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train · 845k rows

modelId stringlengths 5 139	author stringlengths 2 42	last_modified timestamp[us, tz=UTC]date 2020-02-15 11:33:14 2025-06-27 06:27:46	downloads int64 0 223M	likes int64 0 11.7k	library_name stringclasses 499 values	tags sequencelengths 1 4.05k	pipeline_tag stringclasses 54 values	createdAt timestamp[us, tz=UTC]date 2022-03-02 23:29:04 2025-06-27 06:26:25	card stringlengths 11 1.01M
Helsinki-NLP/opus-mt-de-eu	Helsinki-NLP	2023-08-16T11:27:50Z	166	1	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "de", "eu", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- language: - de - eu tags: - translation license: apache-2.0 --- ### deu-eus * source group: German * target group: Basque * OPUS readme: [deu-eus](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/deu-eus/README.md) * model: transformer-align * source language(s): deu * target language(s): eus * model: transformer-align * pre-processing: normalization + SentencePiece (spm12k,spm12k) * download original weights: [opus-2020-06-16.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/deu-eus/opus-2020-06-16.zip) * test set translations: [opus-2020-06-16.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/deu-eus/opus-2020-06-16.test.txt) * test set scores: [opus-2020-06-16.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/deu-eus/opus-2020-06-16.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.deu.eus \| 31.8 \| 0.574 \| ### System Info: - hf_name: deu-eus - source_languages: deu - target_languages: eus - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/deu-eus/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['de', 'eu'] - src_constituents: {'deu'} - tgt_constituents: {'eus'} - src_multilingual: False - tgt_multilingual: False - prepro: normalization + SentencePiece (spm12k,spm12k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/deu-eus/opus-2020-06-16.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/deu-eus/opus-2020-06-16.test.txt - src_alpha3: deu - tgt_alpha3: eus - short_pair: de-eu - chrF2_score: 0.574 - bleu: 31.8 - brevity_penalty: 0.9209999999999999 - ref_len: 2829.0 - src_name: German - tgt_name: Basque - train_date: 2020-06-16 - src_alpha2: de - tgt_alpha2: eu - prefer_old: False - long_pair: deu-eus - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Nextcloud-AI/opus-mt-de-es	Nextcloud-AI	2023-08-16T11:27:48Z	119	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2024-02-23T10:38:02Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-de-es * source languages: de * target languages: es * OPUS readme: [de-es](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/de-es/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-15.zip](https://object.pouta.csc.fi/OPUS-MT-models/de-es/opus-2020-01-15.zip) * test set translations: [opus-2020-01-15.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/de-es/opus-2020-01-15.test.txt) * test set scores: [opus-2020-01-15.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/de-es/opus-2020-01-15.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba.de.es \| 48.5 \| 0.676 \|
Helsinki-NLP/opus-mt-de-es	Helsinki-NLP	2023-08-16T11:27:48Z	32,010	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "de", "es", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-de-es * source languages: de * target languages: es * OPUS readme: [de-es](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/de-es/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-15.zip](https://object.pouta.csc.fi/OPUS-MT-models/de-es/opus-2020-01-15.zip) * test set translations: [opus-2020-01-15.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/de-es/opus-2020-01-15.test.txt) * test set scores: [opus-2020-01-15.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/de-es/opus-2020-01-15.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba.de.es \| 48.5 \| 0.676 \|
Helsinki-NLP/opus-mt-de-en	Helsinki-NLP	2023-08-16T11:27:46Z	673,311	44	transformers	[ "transformers", "pytorch", "tf", "rust", "marian", "text2text-generation", "translation", "de", "en", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-de-en * source languages: de * target languages: en * OPUS readme: [de-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/de-en/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-02-26.zip](https://object.pouta.csc.fi/OPUS-MT-models/de-en/opus-2020-02-26.zip) * test set translations: [opus-2020-02-26.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/de-en/opus-2020-02-26.test.txt) * test set scores: [opus-2020-02-26.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/de-en/opus-2020-02-26.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| newssyscomb2009.de.en \| 29.4 \| 0.557 \| \| news-test2008.de.en \| 27.8 \| 0.548 \| \| newstest2009.de.en \| 26.8 \| 0.543 \| \| newstest2010.de.en \| 30.2 \| 0.584 \| \| newstest2011.de.en \| 27.4 \| 0.556 \| \| newstest2012.de.en \| 29.1 \| 0.569 \| \| newstest2013.de.en \| 32.1 \| 0.583 \| \| newstest2014-deen.de.en \| 34.0 \| 0.600 \| \| newstest2015-ende.de.en \| 34.2 \| 0.599 \| \| newstest2016-ende.de.en \| 40.4 \| 0.649 \| \| newstest2017-ende.de.en \| 35.7 \| 0.610 \| \| newstest2018-ende.de.en \| 43.7 \| 0.667 \| \| newstest2019-deen.de.en \| 40.1 \| 0.642 \| \| Tatoeba.de.en \| 55.4 \| 0.707 \|
Helsinki-NLP/opus-mt-de-efi	Helsinki-NLP	2023-08-16T11:27:43Z	101	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "de", "efi", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-de-efi * source languages: de * target languages: efi * OPUS readme: [de-efi](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/de-efi/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-20.zip](https://object.pouta.csc.fi/OPUS-MT-models/de-efi/opus-2020-01-20.zip) * test set translations: [opus-2020-01-20.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/de-efi/opus-2020-01-20.test.txt) * test set scores: [opus-2020-01-20.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/de-efi/opus-2020-01-20.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| JW300.de.efi \| 24.2 \| 0.451 \|
Helsinki-NLP/opus-mt-de-ee	Helsinki-NLP	2023-08-16T11:27:42Z	113	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "de", "ee", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-de-ee * source languages: de * target languages: ee * OPUS readme: [de-ee](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/de-ee/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-20.zip](https://object.pouta.csc.fi/OPUS-MT-models/de-ee/opus-2020-01-20.zip) * test set translations: [opus-2020-01-20.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/de-ee/opus-2020-01-20.test.txt) * test set scores: [opus-2020-01-20.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/de-ee/opus-2020-01-20.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| JW300.de.ee \| 24.6 \| 0.463 \|
Helsinki-NLP/opus-mt-de-de	Helsinki-NLP	2023-08-16T11:27:41Z	207	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "de", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-de-de * source languages: de * target languages: de * OPUS readme: [de-de](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/de-de/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-20.zip](https://object.pouta.csc.fi/OPUS-MT-models/de-de/opus-2020-01-20.zip) * test set translations: [opus-2020-01-20.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/de-de/opus-2020-01-20.test.txt) * test set scores: [opus-2020-01-20.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/de-de/opus-2020-01-20.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba.de.de \| 40.7 \| 0.616 \|
Helsinki-NLP/opus-mt-de-ca	Helsinki-NLP	2023-08-16T11:27:37Z	181	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "de", "ca", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- language: - de - ca tags: - translation license: apache-2.0 --- ### deu-cat * source group: German * target group: Catalan * OPUS readme: [deu-cat](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/deu-cat/README.md) * model: transformer-align * source language(s): deu * target language(s): cat * model: transformer-align * pre-processing: normalization + SentencePiece (spm12k,spm12k) * download original weights: [opus-2020-06-16.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/deu-cat/opus-2020-06-16.zip) * test set translations: [opus-2020-06-16.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/deu-cat/opus-2020-06-16.test.txt) * test set scores: [opus-2020-06-16.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/deu-cat/opus-2020-06-16.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.deu.cat \| 37.4 \| 0.582 \| ### System Info: - hf_name: deu-cat - source_languages: deu - target_languages: cat - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/deu-cat/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['de', 'ca'] - src_constituents: {'deu'} - tgt_constituents: {'cat'} - src_multilingual: False - tgt_multilingual: False - prepro: normalization + SentencePiece (spm12k,spm12k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/deu-cat/opus-2020-06-16.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/deu-cat/opus-2020-06-16.test.txt - src_alpha3: deu - tgt_alpha3: cat - short_pair: de-ca - chrF2_score: 0.5820000000000001 - bleu: 37.4 - brevity_penalty: 0.956 - ref_len: 5507.0 - src_name: German - tgt_name: Catalan - train_date: 2020-06-16 - src_alpha2: de - tgt_alpha2: ca - prefer_old: False - long_pair: deu-cat - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Helsinki-NLP/opus-mt-de-bi	Helsinki-NLP	2023-08-16T11:27:35Z	110	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "de", "bi", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-de-bi * source languages: de * target languages: bi * OPUS readme: [de-bi](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/de-bi/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-20.zip](https://object.pouta.csc.fi/OPUS-MT-models/de-bi/opus-2020-01-20.zip) * test set translations: [opus-2020-01-20.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/de-bi/opus-2020-01-20.test.txt) * test set scores: [opus-2020-01-20.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/de-bi/opus-2020-01-20.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| JW300.de.bi \| 25.7 \| 0.450 \|
Helsinki-NLP/opus-mt-de-bcl	Helsinki-NLP	2023-08-16T11:27:33Z	105	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "de", "bcl", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-de-bcl * source languages: de * target languages: bcl * OPUS readme: [de-bcl](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/de-bcl/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-20.zip](https://object.pouta.csc.fi/OPUS-MT-models/de-bcl/opus-2020-01-20.zip) * test set translations: [opus-2020-01-20.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/de-bcl/opus-2020-01-20.test.txt) * test set scores: [opus-2020-01-20.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/de-bcl/opus-2020-01-20.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| JW300.de.bcl \| 34.6 \| 0.563 \|
Helsinki-NLP/opus-mt-de-af	Helsinki-NLP	2023-08-16T11:27:29Z	259	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "de", "af", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- language: - de - af tags: - translation license: apache-2.0 --- ### deu-afr * source group: German * target group: Afrikaans * OPUS readme: [deu-afr](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/deu-afr/README.md) * model: transformer-align * source language(s): deu * target language(s): afr * model: transformer-align * pre-processing: normalization + SentencePiece (spm32k,spm32k) * download original weights: [opus-2020-06-17.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/deu-afr/opus-2020-06-17.zip) * test set translations: [opus-2020-06-17.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/deu-afr/opus-2020-06-17.test.txt) * test set scores: [opus-2020-06-17.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/deu-afr/opus-2020-06-17.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.deu.afr \| 51.3 \| 0.690 \| ### System Info: - hf_name: deu-afr - source_languages: deu - target_languages: afr - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/deu-afr/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['de', 'af'] - src_constituents: {'deu'} - tgt_constituents: {'afr'} - src_multilingual: False - tgt_multilingual: False - prepro: normalization + SentencePiece (spm32k,spm32k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/deu-afr/opus-2020-06-17.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/deu-afr/opus-2020-06-17.test.txt - src_alpha3: deu - tgt_alpha3: afr - short_pair: de-af - chrF2_score: 0.69 - bleu: 51.3 - brevity_penalty: 1.0 - ref_len: 9507.0 - src_name: German - tgt_name: Afrikaans - train_date: 2020-06-17 - src_alpha2: de - tgt_alpha2: af - prefer_old: False - long_pair: deu-afr - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Helsinki-NLP/opus-mt-de-ZH	Helsinki-NLP	2023-08-16T11:27:28Z	379	2	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "de", "zh", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-de-ZH * source languages: de * target languages: cmn,cn,yue,ze_zh,zh_cn,zh_CN,zh_HK,zh_tw,zh_TW,zh_yue,zhs,zht,zh * OPUS readme: [de-cmn+cn+yue+ze_zh+zh_cn+zh_CN+zh_HK+zh_tw+zh_TW+zh_yue+zhs+zht+zh](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/de-cmn+cn+yue+ze_zh+zh_cn+zh_CN+zh_HK+zh_tw+zh_TW+zh_yue+zhs+zht+zh/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * a sentence initial language token is required in the form of `>>id<<` (id = valid target language ID) * download original weights: [opus-2020-01-20.zip](https://object.pouta.csc.fi/OPUS-MT-models/de-cmn+cn+yue+ze_zh+zh_cn+zh_CN+zh_HK+zh_tw+zh_TW+zh_yue+zhs+zht+zh/opus-2020-01-20.zip) * test set translations: [opus-2020-01-20.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/de-cmn+cn+yue+ze_zh+zh_cn+zh_CN+zh_HK+zh_tw+zh_TW+zh_yue+zhs+zht+zh/opus-2020-01-20.test.txt) * test set scores: [opus-2020-01-20.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/de-cmn+cn+yue+ze_zh+zh_cn+zh_CN+zh_HK+zh_tw+zh_TW+zh_yue+zhs+zht+zh/opus-2020-01-20.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| bible-uedin.de.zh \| 24.4 \| 0.335 \|
Nextcloud-AI/opus-mt-de-zh	Nextcloud-AI	2023-08-16T11:27:28Z	106	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2024-02-23T10:38:53Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-de-ZH * source languages: de * target languages: cmn,cn,yue,ze_zh,zh_cn,zh_CN,zh_HK,zh_tw,zh_TW,zh_yue,zhs,zht,zh * OPUS readme: [de-cmn+cn+yue+ze_zh+zh_cn+zh_CN+zh_HK+zh_tw+zh_TW+zh_yue+zhs+zht+zh](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/de-cmn+cn+yue+ze_zh+zh_cn+zh_CN+zh_HK+zh_tw+zh_TW+zh_yue+zhs+zht+zh/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * a sentence initial language token is required in the form of `>>id<<` (id = valid target language ID) * download original weights: [opus-2020-01-20.zip](https://object.pouta.csc.fi/OPUS-MT-models/de-cmn+cn+yue+ze_zh+zh_cn+zh_CN+zh_HK+zh_tw+zh_TW+zh_yue+zhs+zht+zh/opus-2020-01-20.zip) * test set translations: [opus-2020-01-20.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/de-cmn+cn+yue+ze_zh+zh_cn+zh_CN+zh_HK+zh_tw+zh_TW+zh_yue+zhs+zht+zh/opus-2020-01-20.test.txt) * test set scores: [opus-2020-01-20.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/de-cmn+cn+yue+ze_zh+zh_cn+zh_CN+zh_HK+zh_tw+zh_TW+zh_yue+zhs+zht+zh/opus-2020-01-20.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| bible-uedin.de.zh \| 24.4 \| 0.335 \|
Helsinki-NLP/opus-mt-da-fi	Helsinki-NLP	2023-08-16T11:27:24Z	315	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "da", "fi", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-da-fi * source languages: da * target languages: fi * OPUS readme: [da-fi](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/da-fi/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-08.zip](https://object.pouta.csc.fi/OPUS-MT-models/da-fi/opus-2020-01-08.zip) * test set translations: [opus-2020-01-08.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/da-fi/opus-2020-01-08.test.txt) * test set scores: [opus-2020-01-08.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/da-fi/opus-2020-01-08.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba.da.fi \| 39.0 \| 0.629 \|
Helsinki-NLP/opus-mt-da-eo	Helsinki-NLP	2023-08-16T11:27:22Z	108	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "da", "eo", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- language: - da - eo tags: - translation license: apache-2.0 --- ### dan-epo * source group: Danish * target group: Esperanto * OPUS readme: [dan-epo](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/dan-epo/README.md) * model: transformer-align * source language(s): dan * target language(s): epo * model: transformer-align * pre-processing: normalization + SentencePiece (spm4k,spm4k) * download original weights: [opus-2020-06-16.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/dan-epo/opus-2020-06-16.zip) * test set translations: [opus-2020-06-16.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/dan-epo/opus-2020-06-16.test.txt) * test set scores: [opus-2020-06-16.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/dan-epo/opus-2020-06-16.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.dan.epo \| 23.6 \| 0.432 \| ### System Info: - hf_name: dan-epo - source_languages: dan - target_languages: epo - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/dan-epo/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['da', 'eo'] - src_constituents: {'dan'} - tgt_constituents: {'epo'} - src_multilingual: False - tgt_multilingual: False - prepro: normalization + SentencePiece (spm4k,spm4k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/dan-epo/opus-2020-06-16.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/dan-epo/opus-2020-06-16.test.txt - src_alpha3: dan - tgt_alpha3: epo - short_pair: da-eo - chrF2_score: 0.43200000000000005 - bleu: 23.6 - brevity_penalty: 0.9420000000000001 - ref_len: 69856.0 - src_name: Danish - tgt_name: Esperanto - train_date: 2020-06-16 - src_alpha2: da - tgt_alpha2: eo - prefer_old: False - long_pair: dan-epo - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Helsinki-NLP/opus-mt-da-de	Helsinki-NLP	2023-08-16T11:27:20Z	16,695	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "da", "de", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-da-de * source languages: da * target languages: de * OPUS readme: [da-de](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/da-de/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-26.zip](https://object.pouta.csc.fi/OPUS-MT-models/da-de/opus-2020-01-26.zip) * test set translations: [opus-2020-01-26.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/da-de/opus-2020-01-26.test.txt) * test set scores: [opus-2020-01-26.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/da-de/opus-2020-01-26.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba.da.de \| 57.4 \| 0.740 \|
Helsinki-NLP/opus-mt-cy-en	Helsinki-NLP	2023-08-16T11:27:19Z	4,822	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "cy", "en", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-cy-en * source languages: cy * target languages: en * OPUS readme: [cy-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/cy-en/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2019-12-18.zip](https://object.pouta.csc.fi/OPUS-MT-models/cy-en/opus-2019-12-18.zip) * test set translations: [opus-2019-12-18.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/cy-en/opus-2019-12-18.test.txt) * test set scores: [opus-2019-12-18.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/cy-en/opus-2019-12-18.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba.cy.en \| 33.0 \| 0.525 \|
Helsinki-NLP/opus-mt-csg-es	Helsinki-NLP	2023-08-16T11:27:15Z	117	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "csg", "es", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-csg-es * source languages: csg * target languages: es * OPUS readme: [csg-es](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/csg-es/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-15.zip](https://object.pouta.csc.fi/OPUS-MT-models/csg-es/opus-2020-01-15.zip) * test set translations: [opus-2020-01-15.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/csg-es/opus-2020-01-15.test.txt) * test set scores: [opus-2020-01-15.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/csg-es/opus-2020-01-15.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| JW300.csg.es \| 93.1 \| 0.952 \|
Helsinki-NLP/opus-mt-cs-uk	Helsinki-NLP	2023-08-16T11:27:14Z	119	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "cs", "uk", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- language: - cs - uk tags: - translation license: apache-2.0 --- ### ces-ukr * source group: Czech * target group: Ukrainian * OPUS readme: [ces-ukr](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ces-ukr/README.md) * model: transformer-align * source language(s): ces * target language(s): ukr * model: transformer-align * pre-processing: normalization + SentencePiece (spm32k,spm32k) * download original weights: [opus-2020-06-17.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/ces-ukr/opus-2020-06-17.zip) * test set translations: [opus-2020-06-17.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/ces-ukr/opus-2020-06-17.test.txt) * test set scores: [opus-2020-06-17.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/ces-ukr/opus-2020-06-17.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.ces.ukr \| 50.9 \| 0.680 \| ### System Info: - hf_name: ces-ukr - source_languages: ces - target_languages: ukr - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ces-ukr/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['cs', 'uk'] - src_constituents: {'ces'} - tgt_constituents: {'ukr'} - src_multilingual: False - tgt_multilingual: False - prepro: normalization + SentencePiece (spm32k,spm32k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/ces-ukr/opus-2020-06-17.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/ces-ukr/opus-2020-06-17.test.txt - src_alpha3: ces - tgt_alpha3: ukr - short_pair: cs-uk - chrF2_score: 0.68 - bleu: 50.9 - brevity_penalty: 0.9940000000000001 - ref_len: 8891.0 - src_name: Czech - tgt_name: Ukrainian - train_date: 2020-06-17 - src_alpha2: cs - tgt_alpha2: uk - prefer_old: False - long_pair: ces-ukr - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Helsinki-NLP/opus-mt-cs-fr	Helsinki-NLP	2023-08-16T11:27:12Z	124	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "cs", "fr", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-cs-fr * source languages: cs * target languages: fr * OPUS readme: [cs-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/cs-fr/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-08.zip](https://object.pouta.csc.fi/OPUS-MT-models/cs-fr/opus-2020-01-08.zip) * test set translations: [opus-2020-01-08.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/cs-fr/opus-2020-01-08.test.txt) * test set scores: [opus-2020-01-08.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/cs-fr/opus-2020-01-08.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| GlobalVoices.cs.fr \| 21.0 \| 0.488 \|
Helsinki-NLP/opus-mt-cs-fi	Helsinki-NLP	2023-08-16T11:27:11Z	117	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "cs", "fi", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-cs-fi * source languages: cs * target languages: fi * OPUS readme: [cs-fi](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/cs-fi/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-08.zip](https://object.pouta.csc.fi/OPUS-MT-models/cs-fi/opus-2020-01-08.zip) * test set translations: [opus-2020-01-08.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/cs-fi/opus-2020-01-08.test.txt) * test set scores: [opus-2020-01-08.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/cs-fi/opus-2020-01-08.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| JW300.cs.fi \| 25.5 \| 0.523 \|
Helsinki-NLP/opus-mt-cs-eo	Helsinki-NLP	2023-08-16T11:27:10Z	111	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "cs", "eo", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- language: - cs - eo tags: - translation license: apache-2.0 --- ### ces-epo * source group: Czech * target group: Esperanto * OPUS readme: [ces-epo](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ces-epo/README.md) * model: transformer-align * source language(s): ces * target language(s): epo * model: transformer-align * pre-processing: normalization + SentencePiece (spm4k,spm4k) * download original weights: [opus-2020-06-16.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/ces-epo/opus-2020-06-16.zip) * test set translations: [opus-2020-06-16.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/ces-epo/opus-2020-06-16.test.txt) * test set scores: [opus-2020-06-16.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/ces-epo/opus-2020-06-16.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.ces.epo \| 26.0 \| 0.459 \| ### System Info: - hf_name: ces-epo - source_languages: ces - target_languages: epo - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ces-epo/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['cs', 'eo'] - src_constituents: {'ces'} - tgt_constituents: {'epo'} - src_multilingual: False - tgt_multilingual: False - prepro: normalization + SentencePiece (spm4k,spm4k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/ces-epo/opus-2020-06-16.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/ces-epo/opus-2020-06-16.test.txt - src_alpha3: ces - tgt_alpha3: epo - short_pair: cs-eo - chrF2_score: 0.45899999999999996 - bleu: 26.0 - brevity_penalty: 0.94 - ref_len: 24901.0 - src_name: Czech - tgt_name: Esperanto - train_date: 2020-06-16 - src_alpha2: cs - tgt_alpha2: eo - prefer_old: False - long_pair: ces-epo - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Helsinki-NLP/opus-mt-crs-fr	Helsinki-NLP	2023-08-16T11:27:06Z	111	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "crs", "fr", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-crs-fr * source languages: crs * target languages: fr * OPUS readme: [crs-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/crs-fr/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-08.zip](https://object.pouta.csc.fi/OPUS-MT-models/crs-fr/opus-2020-01-08.zip) * test set translations: [opus-2020-01-08.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/crs-fr/opus-2020-01-08.test.txt) * test set scores: [opus-2020-01-08.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/crs-fr/opus-2020-01-08.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| JW300.crs.fr \| 29.4 \| 0.475 \|
Helsinki-NLP/opus-mt-crs-fi	Helsinki-NLP	2023-08-16T11:27:05Z	119	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "crs", "fi", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-crs-fi * source languages: crs * target languages: fi * OPUS readme: [crs-fi](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/crs-fi/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-08.zip](https://object.pouta.csc.fi/OPUS-MT-models/crs-fi/opus-2020-01-08.zip) * test set translations: [opus-2020-01-08.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/crs-fi/opus-2020-01-08.test.txt) * test set scores: [opus-2020-01-08.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/crs-fi/opus-2020-01-08.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| JW300.crs.fi \| 25.6 \| 0.479 \|
Helsinki-NLP/opus-mt-crs-de	Helsinki-NLP	2023-08-16T11:27:02Z	112	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "crs", "de", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-crs-de * source languages: crs * target languages: de * OPUS readme: [crs-de](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/crs-de/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-20.zip](https://object.pouta.csc.fi/OPUS-MT-models/crs-de/opus-2020-01-20.zip) * test set translations: [opus-2020-01-20.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/crs-de/opus-2020-01-20.test.txt) * test set scores: [opus-2020-01-20.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/crs-de/opus-2020-01-20.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| JW300.crs.de \| 20.4 \| 0.397 \|
Helsinki-NLP/opus-mt-cpf-en	Helsinki-NLP	2023-08-16T11:26:59Z	112	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "ht", "cpf", "en", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- language: - ht - cpf - en tags: - translation license: apache-2.0 --- ### cpf-eng * source group: Creoles and pidgins, French‑based * target group: English * OPUS readme: [cpf-eng](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/cpf-eng/README.md) * model: transformer * source language(s): gcf_Latn hat mfe * target language(s): eng * model: transformer * pre-processing: normalization + SentencePiece (spm32k,spm32k) * download original weights: [opus2m-2020-07-31.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/cpf-eng/opus2m-2020-07-31.zip) * test set translations: [opus2m-2020-07-31.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/cpf-eng/opus2m-2020-07-31.test.txt) * test set scores: [opus2m-2020-07-31.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/cpf-eng/opus2m-2020-07-31.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.gcf-eng.gcf.eng \| 8.4 \| 0.229 \| \| Tatoeba-test.hat-eng.hat.eng \| 28.0 \| 0.421 \| \| Tatoeba-test.mfe-eng.mfe.eng \| 66.0 \| 0.808 \| \| Tatoeba-test.multi.eng \| 16.3 \| 0.323 \| ### System Info: - hf_name: cpf-eng - source_languages: cpf - target_languages: eng - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/cpf-eng/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['ht', 'cpf', 'en'] - src_constituents: {'gcf_Latn', 'hat', 'mfe'} - tgt_constituents: {'eng'} - src_multilingual: True - tgt_multilingual: False - prepro: normalization + SentencePiece (spm32k,spm32k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/cpf-eng/opus2m-2020-07-31.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/cpf-eng/opus2m-2020-07-31.test.txt - src_alpha3: cpf - tgt_alpha3: eng - short_pair: cpf-en - chrF2_score: 0.32299999999999995 - bleu: 16.3 - brevity_penalty: 1.0 - ref_len: 990.0 - src_name: Creoles and pidgins, French‑based - tgt_name: English - train_date: 2020-07-31 - src_alpha2: cpf - tgt_alpha2: en - prefer_old: False - long_pair: cpf-eng - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Helsinki-NLP/opus-mt-chk-sv	Helsinki-NLP	2023-08-16T11:26:58Z	112	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "chk", "sv", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-chk-sv * source languages: chk * target languages: sv * OPUS readme: [chk-sv](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/chk-sv/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-08.zip](https://object.pouta.csc.fi/OPUS-MT-models/chk-sv/opus-2020-01-08.zip) * test set translations: [opus-2020-01-08.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/chk-sv/opus-2020-01-08.test.txt) * test set scores: [opus-2020-01-08.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/chk-sv/opus-2020-01-08.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| JW300.chk.sv \| 23.6 \| 0.406 \|
Helsinki-NLP/opus-mt-ceb-sv	Helsinki-NLP	2023-08-16T11:26:53Z	111	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "ceb", "sv", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-ceb-sv * source languages: ceb * target languages: sv * OPUS readme: [ceb-sv](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ceb-sv/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-08.zip](https://object.pouta.csc.fi/OPUS-MT-models/ceb-sv/opus-2020-01-08.zip) * test set translations: [opus-2020-01-08.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/ceb-sv/opus-2020-01-08.test.txt) * test set scores: [opus-2020-01-08.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/ceb-sv/opus-2020-01-08.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| JW300.ceb.sv \| 35.5 \| 0.552 \|
Helsinki-NLP/opus-mt-ceb-es	Helsinki-NLP	2023-08-16T11:26:50Z	111	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "ceb", "es", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-ceb-es * source languages: ceb * target languages: es * OPUS readme: [ceb-es](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ceb-es/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-15.zip](https://object.pouta.csc.fi/OPUS-MT-models/ceb-es/opus-2020-01-15.zip) * test set translations: [opus-2020-01-15.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/ceb-es/opus-2020-01-15.test.txt) * test set scores: [opus-2020-01-15.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/ceb-es/opus-2020-01-15.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| JW300.ceb.es \| 31.6 \| 0.508 \|
Helsinki-NLP/opus-mt-ceb-en	Helsinki-NLP	2023-08-16T11:26:49Z	1,276	1	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "ceb", "en", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- language: - ceb - en tags: - translation license: apache-2.0 --- ### ceb-eng * source group: Cebuano * target group: English * OPUS readme: [ceb-eng](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ceb-eng/README.md) * model: transformer-align * source language(s): ceb * target language(s): eng * model: transformer-align * pre-processing: normalization + SentencePiece (spm32k,spm32k) * download original weights: [opus-2020-06-17.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/ceb-eng/opus-2020-06-17.zip) * test set translations: [opus-2020-06-17.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/ceb-eng/opus-2020-06-17.test.txt) * test set scores: [opus-2020-06-17.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/ceb-eng/opus-2020-06-17.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.ceb.eng \| 21.5 \| 0.387 \| ### System Info: - hf_name: ceb-eng - source_languages: ceb - target_languages: eng - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ceb-eng/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['ceb', 'en'] - src_constituents: {'ceb'} - tgt_constituents: {'eng'} - src_multilingual: False - tgt_multilingual: False - prepro: normalization + SentencePiece (spm32k,spm32k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/ceb-eng/opus-2020-06-17.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/ceb-eng/opus-2020-06-17.test.txt - src_alpha3: ceb - tgt_alpha3: eng - short_pair: ceb-en - chrF2_score: 0.387 - bleu: 21.5 - brevity_penalty: 1.0 - ref_len: 2293.0 - src_name: Cebuano - tgt_name: English - train_date: 2020-06-17 - src_alpha2: ceb - tgt_alpha2: en - prefer_old: False - long_pair: ceb-eng - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Helsinki-NLP/opus-mt-cau-en	Helsinki-NLP	2023-08-16T11:26:47Z	119	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "ab", "ka", "ce", "cau", "en", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- language: - ab - ka - ce - cau - en tags: - translation license: apache-2.0 --- ### cau-eng * source group: Caucasian languages * target group: English * OPUS readme: [cau-eng](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/cau-eng/README.md) * model: transformer * source language(s): abk ady che kat * target language(s): eng * model: transformer * pre-processing: normalization + SentencePiece (spm32k,spm32k) * download original weights: [opus2m-2020-07-31.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/cau-eng/opus2m-2020-07-31.zip) * test set translations: [opus2m-2020-07-31.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/cau-eng/opus2m-2020-07-31.test.txt) * test set scores: [opus2m-2020-07-31.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/cau-eng/opus2m-2020-07-31.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.abk-eng.abk.eng \| 0.3 \| 0.134 \| \| Tatoeba-test.ady-eng.ady.eng \| 0.4 \| 0.104 \| \| Tatoeba-test.che-eng.che.eng \| 0.6 \| 0.128 \| \| Tatoeba-test.kat-eng.kat.eng \| 18.6 \| 0.366 \| \| Tatoeba-test.multi.eng \| 16.6 \| 0.351 \| ### System Info: - hf_name: cau-eng - source_languages: cau - target_languages: eng - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/cau-eng/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['ab', 'ka', 'ce', 'cau', 'en'] - src_constituents: {'abk', 'kat', 'che', 'ady'} - tgt_constituents: {'eng'} - src_multilingual: True - tgt_multilingual: False - prepro: normalization + SentencePiece (spm32k,spm32k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/cau-eng/opus2m-2020-07-31.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/cau-eng/opus2m-2020-07-31.test.txt - src_alpha3: cau - tgt_alpha3: eng - short_pair: cau-en - chrF2_score: 0.35100000000000003 - bleu: 16.6 - brevity_penalty: 1.0 - ref_len: 6285.0 - src_name: Caucasian languages - tgt_name: English - train_date: 2020-07-31 - src_alpha2: cau - tgt_alpha2: en - prefer_old: False - long_pair: cau-eng - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Helsinki-NLP/opus-mt-ca-uk	Helsinki-NLP	2023-08-16T11:26:46Z	145	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "ca", "uk", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- language: - ca - uk tags: - translation license: apache-2.0 --- ### cat-ukr * source group: Catalan * target group: Ukrainian * OPUS readme: [cat-ukr](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/cat-ukr/README.md) * model: transformer-align * source language(s): cat * target language(s): ukr * model: transformer-align * pre-processing: normalization + SentencePiece (spm4k,spm4k) * download original weights: [opus-2020-06-16.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/cat-ukr/opus-2020-06-16.zip) * test set translations: [opus-2020-06-16.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/cat-ukr/opus-2020-06-16.test.txt) * test set scores: [opus-2020-06-16.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/cat-ukr/opus-2020-06-16.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.cat.ukr \| 28.6 \| 0.503 \| ### System Info: - hf_name: cat-ukr - source_languages: cat - target_languages: ukr - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/cat-ukr/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['ca', 'uk'] - src_constituents: {'cat'} - tgt_constituents: {'ukr'} - src_multilingual: False - tgt_multilingual: False - prepro: normalization + SentencePiece (spm4k,spm4k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/cat-ukr/opus-2020-06-16.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/cat-ukr/opus-2020-06-16.test.txt - src_alpha3: cat - tgt_alpha3: ukr - short_pair: ca-uk - chrF2_score: 0.503 - bleu: 28.6 - brevity_penalty: 0.9670000000000001 - ref_len: 2438.0 - src_name: Catalan - tgt_name: Ukrainian - train_date: 2020-06-16 - src_alpha2: ca - tgt_alpha2: uk - prefer_old: False - long_pair: cat-ukr - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Helsinki-NLP/opus-mt-ca-pt	Helsinki-NLP	2023-08-16T11:26:45Z	132	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "ca", "pt", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- language: - ca - pt tags: - translation license: apache-2.0 --- ### cat-por * source group: Catalan * target group: Portuguese * OPUS readme: [cat-por](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/cat-por/README.md) * model: transformer-align * source language(s): cat * target language(s): por * model: transformer-align * pre-processing: normalization + SentencePiece (spm12k,spm12k) * download original weights: [opus-2020-06-17.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/cat-por/opus-2020-06-17.zip) * test set translations: [opus-2020-06-17.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/cat-por/opus-2020-06-17.test.txt) * test set scores: [opus-2020-06-17.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/cat-por/opus-2020-06-17.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.cat.por \| 44.9 \| 0.658 \| ### System Info: - hf_name: cat-por - source_languages: cat - target_languages: por - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/cat-por/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['ca', 'pt'] - src_constituents: {'cat'} - tgt_constituents: {'por'} - src_multilingual: False - tgt_multilingual: False - prepro: normalization + SentencePiece (spm12k,spm12k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/cat-por/opus-2020-06-17.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/cat-por/opus-2020-06-17.test.txt - src_alpha3: cat - tgt_alpha3: por - short_pair: ca-pt - chrF2_score: 0.6579999999999999 - bleu: 44.9 - brevity_penalty: 0.953 - ref_len: 5847.0 - src_name: Catalan - tgt_name: Portuguese - train_date: 2020-06-17 - src_alpha2: ca - tgt_alpha2: pt - prefer_old: False - long_pair: cat-por - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Helsinki-NLP/opus-mt-ca-es	Helsinki-NLP	2023-08-16T11:26:40Z	832	1	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "ca", "es", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-ca-es * source languages: ca * target languages: es * OPUS readme: [ca-es](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ca-es/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-15.zip](https://object.pouta.csc.fi/OPUS-MT-models/ca-es/opus-2020-01-15.zip) * test set translations: [opus-2020-01-15.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/ca-es/opus-2020-01-15.test.txt) * test set scores: [opus-2020-01-15.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/ca-es/opus-2020-01-15.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba.ca.es \| 74.9 \| 0.863 \|
Helsinki-NLP/opus-mt-ca-en	Helsinki-NLP	2023-08-16T11:26:39Z	8,325	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "ca", "en", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-ca-en * source languages: ca * target languages: en * OPUS readme: [ca-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ca-en/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2019-12-18.zip](https://object.pouta.csc.fi/OPUS-MT-models/ca-en/opus-2019-12-18.zip) * test set translations: [opus-2019-12-18.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/ca-en/opus-2019-12-18.test.txt) * test set scores: [opus-2019-12-18.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/ca-en/opus-2019-12-18.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba.ca.en \| 51.4 \| 0.678 \|
Helsinki-NLP/opus-mt-bzs-sv	Helsinki-NLP	2023-08-16T11:26:37Z	122	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "bzs", "sv", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-bzs-sv * source languages: bzs * target languages: sv * OPUS readme: [bzs-sv](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/bzs-sv/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-08.zip](https://object.pouta.csc.fi/OPUS-MT-models/bzs-sv/opus-2020-01-08.zip) * test set translations: [opus-2020-01-08.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/bzs-sv/opus-2020-01-08.test.txt) * test set scores: [opus-2020-01-08.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/bzs-sv/opus-2020-01-08.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| JW300.bzs.sv \| 30.7 \| 0.489 \|
Helsinki-NLP/opus-mt-bzs-en	Helsinki-NLP	2023-08-16T11:26:32Z	261	1	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "bzs", "en", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-bzs-en * source languages: bzs * target languages: en * OPUS readme: [bzs-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/bzs-en/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2019-12-18.zip](https://object.pouta.csc.fi/OPUS-MT-models/bzs-en/opus-2019-12-18.zip) * test set translations: [opus-2019-12-18.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/bzs-en/opus-2019-12-18.test.txt) * test set scores: [opus-2019-12-18.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/bzs-en/opus-2019-12-18.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| JW300.bzs.en \| 44.5 \| 0.605 \|
Helsinki-NLP/opus-mt-bnt-en	Helsinki-NLP	2023-08-16T11:26:31Z	198	2	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "sn", "zu", "rw", "lg", "ts", "ln", "ny", "xh", "rn", "bnt", "en", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- language: - sn - zu - rw - lg - ts - ln - ny - xh - rn - bnt - en tags: - translation license: apache-2.0 --- ### bnt-eng * source group: Bantu languages * target group: English * OPUS readme: [bnt-eng](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/bnt-eng/README.md) * model: transformer * source language(s): kin lin lug nya run sna swh toi_Latn tso umb xho zul * target language(s): eng * model: transformer * pre-processing: normalization + SentencePiece (spm32k,spm32k) * download original weights: [opus2m-2020-07-31.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/bnt-eng/opus2m-2020-07-31.zip) * test set translations: [opus2m-2020-07-31.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/bnt-eng/opus2m-2020-07-31.test.txt) * test set scores: [opus2m-2020-07-31.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/bnt-eng/opus2m-2020-07-31.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.kin-eng.kin.eng \| 31.7 \| 0.481 \| \| Tatoeba-test.lin-eng.lin.eng \| 8.3 \| 0.271 \| \| Tatoeba-test.lug-eng.lug.eng \| 5.3 \| 0.128 \| \| Tatoeba-test.multi.eng \| 23.1 \| 0.394 \| \| Tatoeba-test.nya-eng.nya.eng \| 38.3 \| 0.527 \| \| Tatoeba-test.run-eng.run.eng \| 26.6 \| 0.431 \| \| Tatoeba-test.sna-eng.sna.eng \| 27.5 \| 0.440 \| \| Tatoeba-test.swa-eng.swa.eng \| 4.6 \| 0.195 \| \| Tatoeba-test.toi-eng.toi.eng \| 16.2 \| 0.342 \| \| Tatoeba-test.tso-eng.tso.eng \| 100.0 \| 1.000 \| \| Tatoeba-test.umb-eng.umb.eng \| 8.4 \| 0.231 \| \| Tatoeba-test.xho-eng.xho.eng \| 37.2 \| 0.554 \| \| Tatoeba-test.zul-eng.zul.eng \| 40.9 \| 0.576 \| ### System Info: - hf_name: bnt-eng - source_languages: bnt - target_languages: eng - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/bnt-eng/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['sn', 'zu', 'rw', 'lg', 'ts', 'ln', 'ny', 'xh', 'rn', 'bnt', 'en'] - src_constituents: {'sna', 'zul', 'kin', 'lug', 'tso', 'lin', 'nya', 'xho', 'swh', 'run', 'toi_Latn', 'umb'} - tgt_constituents: {'eng'} - src_multilingual: True - tgt_multilingual: False - prepro: normalization + SentencePiece (spm32k,spm32k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/bnt-eng/opus2m-2020-07-31.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/bnt-eng/opus2m-2020-07-31.test.txt - src_alpha3: bnt - tgt_alpha3: eng - short_pair: bnt-en - chrF2_score: 0.39399999999999996 - bleu: 23.1 - brevity_penalty: 1.0 - ref_len: 14565.0 - src_name: Bantu languages - tgt_name: English - train_date: 2020-07-31 - src_alpha2: bnt - tgt_alpha2: en - prefer_old: False - long_pair: bnt-eng - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Helsinki-NLP/opus-mt-bi-fr	Helsinki-NLP	2023-08-16T11:26:28Z	109	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "bi", "fr", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-bi-fr * source languages: bi * target languages: fr * OPUS readme: [bi-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/bi-fr/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-20.zip](https://object.pouta.csc.fi/OPUS-MT-models/bi-fr/opus-2020-01-20.zip) * test set translations: [opus-2020-01-20.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/bi-fr/opus-2020-01-20.test.txt) * test set scores: [opus-2020-01-20.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/bi-fr/opus-2020-01-20.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| JW300.bi.fr \| 21.5 \| 0.382 \|
Helsinki-NLP/opus-mt-bi-es	Helsinki-NLP	2023-08-16T11:26:27Z	112	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "bi", "es", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-bi-es * source languages: bi * target languages: es * OPUS readme: [bi-es](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/bi-es/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-20.zip](https://object.pouta.csc.fi/OPUS-MT-models/bi-es/opus-2020-01-20.zip) * test set translations: [opus-2020-01-20.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/bi-es/opus-2020-01-20.test.txt) * test set scores: [opus-2020-01-20.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/bi-es/opus-2020-01-20.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| JW300.bi.es \| 21.1 \| 0.388 \|
Helsinki-NLP/opus-mt-bi-en	Helsinki-NLP	2023-08-16T11:26:26Z	142	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "bi", "en", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-bi-en * source languages: bi * target languages: en * OPUS readme: [bi-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/bi-en/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-20.zip](https://object.pouta.csc.fi/OPUS-MT-models/bi-en/opus-2020-01-20.zip) * test set translations: [opus-2020-01-20.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/bi-en/opus-2020-01-20.test.txt) * test set scores: [opus-2020-01-20.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/bi-en/opus-2020-01-20.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| JW300.bi.en \| 30.3 \| 0.458 \|
Helsinki-NLP/opus-mt-bg-uk	Helsinki-NLP	2023-08-16T11:26:25Z	139	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "bg", "uk", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- language: - bg - uk tags: - translation license: apache-2.0 --- ### bul-ukr * source group: Bulgarian * target group: Ukrainian * OPUS readme: [bul-ukr](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/bul-ukr/README.md) * model: transformer-align * source language(s): bul * target language(s): ukr * model: transformer-align * pre-processing: normalization + SentencePiece (spm32k,spm32k) * download original weights: [opus-2020-06-17.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/bul-ukr/opus-2020-06-17.zip) * test set translations: [opus-2020-06-17.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/bul-ukr/opus-2020-06-17.test.txt) * test set scores: [opus-2020-06-17.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/bul-ukr/opus-2020-06-17.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.bul.ukr \| 49.2 \| 0.683 \| ### System Info: - hf_name: bul-ukr - source_languages: bul - target_languages: ukr - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/bul-ukr/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['bg', 'uk'] - src_constituents: {'bul', 'bul_Latn'} - tgt_constituents: {'ukr'} - src_multilingual: False - tgt_multilingual: False - prepro: normalization + SentencePiece (spm32k,spm32k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/bul-ukr/opus-2020-06-17.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/bul-ukr/opus-2020-06-17.test.txt - src_alpha3: bul - tgt_alpha3: ukr - short_pair: bg-uk - chrF2_score: 0.6829999999999999 - bleu: 49.2 - brevity_penalty: 0.983 - ref_len: 4932.0 - src_name: Bulgarian - tgt_name: Ukrainian - train_date: 2020-06-17 - src_alpha2: bg - tgt_alpha2: uk - prefer_old: False - long_pair: bul-ukr - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Helsinki-NLP/opus-mt-bg-tr	Helsinki-NLP	2023-08-16T11:26:23Z	114	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "bg", "tr", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- language: - bg - tr tags: - translation license: apache-2.0 --- ### bul-tur * source group: Bulgarian * target group: Turkish * OPUS readme: [bul-tur](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/bul-tur/README.md) * model: transformer * source language(s): bul bul_Latn * target language(s): tur * model: transformer * pre-processing: normalization + SentencePiece (spm32k,spm32k) * download original weights: [opus-2020-07-03.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/bul-tur/opus-2020-07-03.zip) * test set translations: [opus-2020-07-03.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/bul-tur/opus-2020-07-03.test.txt) * test set scores: [opus-2020-07-03.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/bul-tur/opus-2020-07-03.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.bul.tur \| 40.9 \| 0.687 \| ### System Info: - hf_name: bul-tur - source_languages: bul - target_languages: tur - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/bul-tur/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['bg', 'tr'] - src_constituents: {'bul', 'bul_Latn'} - tgt_constituents: {'tur'} - src_multilingual: False - tgt_multilingual: False - prepro: normalization + SentencePiece (spm32k,spm32k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/bul-tur/opus-2020-07-03.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/bul-tur/opus-2020-07-03.test.txt - src_alpha3: bul - tgt_alpha3: tur - short_pair: bg-tr - chrF2_score: 0.687 - bleu: 40.9 - brevity_penalty: 0.946 - ref_len: 4948.0 - src_name: Bulgarian - tgt_name: Turkish - train_date: 2020-07-03 - src_alpha2: bg - tgt_alpha2: tr - prefer_old: False - long_pair: bul-tur - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Helsinki-NLP/opus-mt-bg-sv	Helsinki-NLP	2023-08-16T11:26:22Z	119	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "bg", "sv", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-bg-sv * source languages: bg * target languages: sv * OPUS readme: [bg-sv](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/bg-sv/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-08.zip](https://object.pouta.csc.fi/OPUS-MT-models/bg-sv/opus-2020-01-08.zip) * test set translations: [opus-2020-01-08.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/bg-sv/opus-2020-01-08.test.txt) * test set scores: [opus-2020-01-08.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/bg-sv/opus-2020-01-08.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| JW300.bg.sv \| 29.1 \| 0.494 \|
Helsinki-NLP/opus-mt-bg-it	Helsinki-NLP	2023-08-16T11:26:20Z	115	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "bg", "it", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- language: - bg - it tags: - translation license: apache-2.0 --- ### bul-ita * source group: Bulgarian * target group: Italian * OPUS readme: [bul-ita](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/bul-ita/README.md) * model: transformer * source language(s): bul * target language(s): ita * model: transformer * pre-processing: normalization + SentencePiece (spm32k,spm32k) * download original weights: [opus-2020-07-03.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/bul-ita/opus-2020-07-03.zip) * test set translations: [opus-2020-07-03.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/bul-ita/opus-2020-07-03.test.txt) * test set scores: [opus-2020-07-03.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/bul-ita/opus-2020-07-03.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.bul.ita \| 43.1 \| 0.653 \| ### System Info: - hf_name: bul-ita - source_languages: bul - target_languages: ita - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/bul-ita/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['bg', 'it'] - src_constituents: {'bul', 'bul_Latn'} - tgt_constituents: {'ita'} - src_multilingual: False - tgt_multilingual: False - prepro: normalization + SentencePiece (spm32k,spm32k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/bul-ita/opus-2020-07-03.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/bul-ita/opus-2020-07-03.test.txt - src_alpha3: bul - tgt_alpha3: ita - short_pair: bg-it - chrF2_score: 0.653 - bleu: 43.1 - brevity_penalty: 0.987 - ref_len: 16951.0 - src_name: Bulgarian - tgt_name: Italian - train_date: 2020-07-03 - src_alpha2: bg - tgt_alpha2: it - prefer_old: False - long_pair: bul-ita - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Helsinki-NLP/opus-mt-bg-fr	Helsinki-NLP	2023-08-16T11:26:19Z	160	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "bg", "fr", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- language: - bg - fr tags: - translation license: apache-2.0 --- ### bul-fra * source group: Bulgarian * target group: French * OPUS readme: [bul-fra](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/bul-fra/README.md) * model: transformer * source language(s): bul * target language(s): fra * model: transformer * pre-processing: normalization + SentencePiece (spm32k,spm32k) * download original weights: [opus-2020-07-03.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/bul-fra/opus-2020-07-03.zip) * test set translations: [opus-2020-07-03.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/bul-fra/opus-2020-07-03.test.txt) * test set scores: [opus-2020-07-03.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/bul-fra/opus-2020-07-03.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.bul.fra \| 53.7 \| 0.693 \| ### System Info: - hf_name: bul-fra - source_languages: bul - target_languages: fra - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/bul-fra/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['bg', 'fr'] - src_constituents: {'bul', 'bul_Latn'} - tgt_constituents: {'fra'} - src_multilingual: False - tgt_multilingual: False - prepro: normalization + SentencePiece (spm32k,spm32k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/bul-fra/opus-2020-07-03.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/bul-fra/opus-2020-07-03.test.txt - src_alpha3: bul - tgt_alpha3: fra - short_pair: bg-fr - chrF2_score: 0.693 - bleu: 53.7 - brevity_penalty: 0.977 - ref_len: 3669.0 - src_name: Bulgarian - tgt_name: French - train_date: 2020-07-03 - src_alpha2: bg - tgt_alpha2: fr - prefer_old: False - long_pair: bul-fra - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Helsinki-NLP/opus-mt-bg-eo	Helsinki-NLP	2023-08-16T11:26:15Z	114	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "bg", "eo", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- language: - bg - eo tags: - translation license: apache-2.0 --- ### bul-epo * source group: Bulgarian * target group: Esperanto * OPUS readme: [bul-epo](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/bul-epo/README.md) * model: transformer-align * source language(s): bul * target language(s): epo * model: transformer-align * pre-processing: normalization + SentencePiece (spm4k,spm4k) * download original weights: [opus-2020-06-16.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/bul-epo/opus-2020-06-16.zip) * test set translations: [opus-2020-06-16.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/bul-epo/opus-2020-06-16.test.txt) * test set scores: [opus-2020-06-16.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/bul-epo/opus-2020-06-16.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.bul.epo \| 24.5 \| 0.438 \| ### System Info: - hf_name: bul-epo - source_languages: bul - target_languages: epo - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/bul-epo/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['bg', 'eo'] - src_constituents: {'bul', 'bul_Latn'} - tgt_constituents: {'epo'} - src_multilingual: False - tgt_multilingual: False - prepro: normalization + SentencePiece (spm4k,spm4k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/bul-epo/opus-2020-06-16.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/bul-epo/opus-2020-06-16.test.txt - src_alpha3: bul - tgt_alpha3: epo - short_pair: bg-eo - chrF2_score: 0.43799999999999994 - bleu: 24.5 - brevity_penalty: 0.9670000000000001 - ref_len: 4043.0 - src_name: Bulgarian - tgt_name: Esperanto - train_date: 2020-06-16 - src_alpha2: bg - tgt_alpha2: eo - prefer_old: False - long_pair: bul-epo - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Helsinki-NLP/opus-mt-bg-de	Helsinki-NLP	2023-08-16T11:26:13Z	123	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "bg", "de", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- language: - bg - de tags: - translation license: apache-2.0 --- ### bul-deu * source group: Bulgarian * target group: German * OPUS readme: [bul-deu](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/bul-deu/README.md) * model: transformer * source language(s): bul * target language(s): deu * model: transformer * pre-processing: normalization + SentencePiece (spm32k,spm32k) * download original weights: [opus-2020-07-03.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/bul-deu/opus-2020-07-03.zip) * test set translations: [opus-2020-07-03.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/bul-deu/opus-2020-07-03.test.txt) * test set scores: [opus-2020-07-03.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/bul-deu/opus-2020-07-03.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.bul.deu \| 49.3 \| 0.676 \| ### System Info: - hf_name: bul-deu - source_languages: bul - target_languages: deu - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/bul-deu/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['bg', 'de'] - src_constituents: {'bul', 'bul_Latn'} - tgt_constituents: {'deu'} - src_multilingual: False - tgt_multilingual: False - prepro: normalization + SentencePiece (spm32k,spm32k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/bul-deu/opus-2020-07-03.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/bul-deu/opus-2020-07-03.test.txt - src_alpha3: bul - tgt_alpha3: deu - short_pair: bg-de - chrF2_score: 0.6759999999999999 - bleu: 49.3 - brevity_penalty: 1.0 - ref_len: 2218.0 - src_name: Bulgarian - tgt_name: German - train_date: 2020-07-03 - src_alpha2: bg - tgt_alpha2: de - prefer_old: False - long_pair: bul-deu - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Helsinki-NLP/opus-mt-ber-fr	Helsinki-NLP	2023-08-16T11:26:12Z	133	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "ber", "fr", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-ber-fr * source languages: ber * target languages: fr * OPUS readme: [ber-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ber-fr/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-08.zip](https://object.pouta.csc.fi/OPUS-MT-models/ber-fr/opus-2020-01-08.zip) * test set translations: [opus-2020-01-08.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/ber-fr/opus-2020-01-08.test.txt) * test set scores: [opus-2020-01-08.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/ber-fr/opus-2020-01-08.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba.ber.fr \| 60.2 \| 0.754 \|
Helsinki-NLP/opus-mt-ber-es	Helsinki-NLP	2023-08-16T11:26:11Z	119	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "ber", "es", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-ber-es * source languages: ber * target languages: es * OPUS readme: [ber-es](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ber-es/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-15.zip](https://object.pouta.csc.fi/OPUS-MT-models/ber-es/opus-2020-01-15.zip) * test set translations: [opus-2020-01-15.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/ber-es/opus-2020-01-15.test.txt) * test set scores: [opus-2020-01-15.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/ber-es/opus-2020-01-15.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba.ber.es \| 33.8 \| 0.487 \|
Helsinki-NLP/opus-mt-ber-en	Helsinki-NLP	2023-08-16T11:26:10Z	138	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "ber", "en", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-ber-en * source languages: ber * target languages: en * OPUS readme: [ber-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ber-en/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2019-12-18.zip](https://object.pouta.csc.fi/OPUS-MT-models/ber-en/opus-2019-12-18.zip) * test set translations: [opus-2019-12-18.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/ber-en/opus-2019-12-18.test.txt) * test set scores: [opus-2019-12-18.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/ber-en/opus-2019-12-18.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba.ber.en \| 37.3 \| 0.566 \|
Helsinki-NLP/opus-mt-bem-fi	Helsinki-NLP	2023-08-16T11:26:07Z	113	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "bem", "fi", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-bem-fi * source languages: bem * target languages: fi * OPUS readme: [bem-fi](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/bem-fi/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-08.zip](https://object.pouta.csc.fi/OPUS-MT-models/bem-fi/opus-2020-01-08.zip) * test set translations: [opus-2020-01-08.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/bem-fi/opus-2020-01-08.test.txt) * test set scores: [opus-2020-01-08.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/bem-fi/opus-2020-01-08.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| JW300.bem.fi \| 22.8 \| 0.439 \|
Helsinki-NLP/opus-mt-bcl-fr	Helsinki-NLP	2023-08-16T11:26:02Z	106	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "bcl", "fr", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-bcl-fr * source languages: bcl * target languages: fr * OPUS readme: [bcl-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/bcl-fr/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-08.zip](https://object.pouta.csc.fi/OPUS-MT-models/bcl-fr/opus-2020-01-08.zip) * test set translations: [opus-2020-01-08.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/bcl-fr/opus-2020-01-08.test.txt) * test set scores: [opus-2020-01-08.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/bcl-fr/opus-2020-01-08.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| JW300.bcl.fr \| 35.0 \| 0.527 \|
Helsinki-NLP/opus-mt-bat-en	Helsinki-NLP	2023-08-16T11:25:57Z	134	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "lt", "lv", "bat", "en", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- language: - lt - lv - bat - en tags: - translation license: apache-2.0 --- ### bat-eng * source group: Baltic languages * target group: English * OPUS readme: [bat-eng](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/bat-eng/README.md) * model: transformer * source language(s): lav lit ltg prg_Latn sgs * target language(s): eng * model: transformer * pre-processing: normalization + SentencePiece (spm32k,spm32k) * download original weights: [opus2m-2020-07-31.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/bat-eng/opus2m-2020-07-31.zip) * test set translations: [opus2m-2020-07-31.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/bat-eng/opus2m-2020-07-31.test.txt) * test set scores: [opus2m-2020-07-31.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/bat-eng/opus2m-2020-07-31.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| newsdev2017-enlv-laveng.lav.eng \| 27.5 \| 0.566 \| \| newsdev2019-enlt-liteng.lit.eng \| 27.8 \| 0.557 \| \| newstest2017-enlv-laveng.lav.eng \| 21.1 \| 0.512 \| \| newstest2019-lten-liteng.lit.eng \| 30.2 \| 0.592 \| \| Tatoeba-test.lav-eng.lav.eng \| 51.5 \| 0.687 \| \| Tatoeba-test.lit-eng.lit.eng \| 55.1 \| 0.703 \| \| Tatoeba-test.multi.eng \| 50.6 \| 0.662 \| \| Tatoeba-test.prg-eng.prg.eng \| 1.0 \| 0.159 \| \| Tatoeba-test.sgs-eng.sgs.eng \| 16.5 \| 0.265 \| ### System Info: - hf_name: bat-eng - source_languages: bat - target_languages: eng - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/bat-eng/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['lt', 'lv', 'bat', 'en'] - src_constituents: {'lit', 'lav', 'prg_Latn', 'ltg', 'sgs'} - tgt_constituents: {'eng'} - src_multilingual: True - tgt_multilingual: False - prepro: normalization + SentencePiece (spm32k,spm32k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/bat-eng/opus2m-2020-07-31.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/bat-eng/opus2m-2020-07-31.test.txt - src_alpha3: bat - tgt_alpha3: eng - short_pair: bat-en - chrF2_score: 0.662 - bleu: 50.6 - brevity_penalty: 0.9890000000000001 - ref_len: 30772.0 - src_name: Baltic languages - tgt_name: English - train_date: 2020-07-31 - src_alpha2: bat - tgt_alpha2: en - prefer_old: False - long_pair: bat-eng - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Helsinki-NLP/opus-mt-az-tr	Helsinki-NLP	2023-08-16T11:25:56Z	344	1	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "az", "tr", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- language: - az - tr tags: - translation license: apache-2.0 --- ### aze-tur * source group: Azerbaijani * target group: Turkish * OPUS readme: [aze-tur](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/aze-tur/README.md) * model: transformer-align * source language(s): aze_Latn * target language(s): tur * model: transformer-align * pre-processing: normalization + SentencePiece (spm4k,spm4k) * download original weights: [opus-2020-06-16.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/aze-tur/opus-2020-06-16.zip) * test set translations: [opus-2020-06-16.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/aze-tur/opus-2020-06-16.test.txt) * test set scores: [opus-2020-06-16.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/aze-tur/opus-2020-06-16.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.aze.tur \| 24.4 \| 0.529 \| ### System Info: - hf_name: aze-tur - source_languages: aze - target_languages: tur - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/aze-tur/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['az', 'tr'] - src_constituents: {'aze_Latn'} - tgt_constituents: {'tur'} - src_multilingual: False - tgt_multilingual: False - prepro: normalization + SentencePiece (spm4k,spm4k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/aze-tur/opus-2020-06-16.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/aze-tur/opus-2020-06-16.test.txt - src_alpha3: aze - tgt_alpha3: tur - short_pair: az-tr - chrF2_score: 0.529 - bleu: 24.4 - brevity_penalty: 0.956 - ref_len: 5380.0 - src_name: Azerbaijani - tgt_name: Turkish - train_date: 2020-06-16 - src_alpha2: az - tgt_alpha2: tr - prefer_old: False - long_pair: aze-tur - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Helsinki-NLP/opus-mt-ase-sv	Helsinki-NLP	2023-08-16T11:25:52Z	127	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "ase", "sv", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-ase-sv * source languages: ase * target languages: sv * OPUS readme: [ase-sv](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ase-sv/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-20.zip](https://object.pouta.csc.fi/OPUS-MT-models/ase-sv/opus-2020-01-20.zip) * test set translations: [opus-2020-01-20.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/ase-sv/opus-2020-01-20.test.txt) * test set scores: [opus-2020-01-20.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/ase-sv/opus-2020-01-20.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| JW300.ase.sv \| 39.7 \| 0.576 \|
Helsinki-NLP/opus-mt-ase-en	Helsinki-NLP	2023-08-16T11:25:49Z	137	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "ase", "en", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-ase-en * source languages: ase * target languages: en * OPUS readme: [ase-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ase-en/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-20.zip](https://object.pouta.csc.fi/OPUS-MT-models/ase-en/opus-2020-01-20.zip) * test set translations: [opus-2020-01-20.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/ase-en/opus-2020-01-20.test.txt) * test set scores: [opus-2020-01-20.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/ase-en/opus-2020-01-20.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| JW300.ase.en \| 99.5 \| 0.997 \|
Nextcloud-AI/opus-mt-ar-tr	Nextcloud-AI	2023-08-16T11:25:46Z	101	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "ar", "tr", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2024-02-23T10:37:39Z	--- language: - ar - tr tags: - translation license: apache-2.0 --- ### ara-tur * source group: Arabic * target group: Turkish * OPUS readme: [ara-tur](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ara-tur/README.md) * model: transformer * source language(s): apc_Latn ara ara_Latn arq_Latn * target language(s): tur * model: transformer * pre-processing: normalization + SentencePiece (spm32k,spm32k) * download original weights: [opus-2020-07-03.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/ara-tur/opus-2020-07-03.zip) * test set translations: [opus-2020-07-03.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/ara-tur/opus-2020-07-03.test.txt) * test set scores: [opus-2020-07-03.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/ara-tur/opus-2020-07-03.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.ara.tur \| 33.1 \| 0.619 \| ### System Info: - hf_name: ara-tur - source_languages: ara - target_languages: tur - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ara-tur/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['ar', 'tr'] - src_constituents: {'apc', 'ara', 'arq_Latn', 'arq', 'afb', 'ara_Latn', 'apc_Latn', 'arz'} - tgt_constituents: {'tur'} - src_multilingual: False - tgt_multilingual: False - prepro: normalization + SentencePiece (spm32k,spm32k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/ara-tur/opus-2020-07-03.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/ara-tur/opus-2020-07-03.test.txt - src_alpha3: ara - tgt_alpha3: tur - short_pair: ar-tr - chrF2_score: 0.619 - bleu: 33.1 - brevity_penalty: 0.9570000000000001 - ref_len: 6949.0 - src_name: Arabic - tgt_name: Turkish - train_date: 2020-07-03 - src_alpha2: ar - tgt_alpha2: tr - prefer_old: False - long_pair: ara-tur - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Helsinki-NLP/opus-mt-ar-it	Helsinki-NLP	2023-08-16T11:25:43Z	250	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "ar", "it", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- language: - ar - it tags: - translation license: apache-2.0 --- ### ara-ita * source group: Arabic * target group: Italian * OPUS readme: [ara-ita](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ara-ita/README.md) * model: transformer * source language(s): ara * target language(s): ita * model: transformer * pre-processing: normalization + SentencePiece (spm32k,spm32k) * download original weights: [opus-2020-07-03.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/ara-ita/opus-2020-07-03.zip) * test set translations: [opus-2020-07-03.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/ara-ita/opus-2020-07-03.test.txt) * test set scores: [opus-2020-07-03.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/ara-ita/opus-2020-07-03.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.ara.ita \| 44.2 \| 0.658 \| ### System Info: - hf_name: ara-ita - source_languages: ara - target_languages: ita - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ara-ita/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['ar', 'it'] - src_constituents: {'apc', 'ara', 'arq_Latn', 'arq', 'afb', 'ara_Latn', 'apc_Latn', 'arz'} - tgt_constituents: {'ita'} - src_multilingual: False - tgt_multilingual: False - prepro: normalization + SentencePiece (spm32k,spm32k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/ara-ita/opus-2020-07-03.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/ara-ita/opus-2020-07-03.test.txt - src_alpha3: ara - tgt_alpha3: ita - short_pair: ar-it - chrF2_score: 0.6579999999999999 - bleu: 44.2 - brevity_penalty: 0.9890000000000001 - ref_len: 1495.0 - src_name: Arabic - tgt_name: Italian - train_date: 2020-07-03 - src_alpha2: ar - tgt_alpha2: it - prefer_old: False - long_pair: ara-ita - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Nextcloud-AI/opus-mt-ar-it	Nextcloud-AI	2023-08-16T11:25:43Z	111	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "ar", "it", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2024-02-23T10:37:30Z	--- language: - ar - it tags: - translation license: apache-2.0 --- ### ara-ita * source group: Arabic * target group: Italian * OPUS readme: [ara-ita](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ara-ita/README.md) * model: transformer * source language(s): ara * target language(s): ita * model: transformer * pre-processing: normalization + SentencePiece (spm32k,spm32k) * download original weights: [opus-2020-07-03.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/ara-ita/opus-2020-07-03.zip) * test set translations: [opus-2020-07-03.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/ara-ita/opus-2020-07-03.test.txt) * test set scores: [opus-2020-07-03.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/ara-ita/opus-2020-07-03.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.ara.ita \| 44.2 \| 0.658 \| ### System Info: - hf_name: ara-ita - source_languages: ara - target_languages: ita - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ara-ita/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['ar', 'it'] - src_constituents: {'apc', 'ara', 'arq_Latn', 'arq', 'afb', 'ara_Latn', 'apc_Latn', 'arz'} - tgt_constituents: {'ita'} - src_multilingual: False - tgt_multilingual: False - prepro: normalization + SentencePiece (spm32k,spm32k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/ara-ita/opus-2020-07-03.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/ara-ita/opus-2020-07-03.test.txt - src_alpha3: ara - tgt_alpha3: ita - short_pair: ar-it - chrF2_score: 0.6579999999999999 - bleu: 44.2 - brevity_penalty: 0.9890000000000001 - ref_len: 1495.0 - src_name: Arabic - tgt_name: Italian - train_date: 2020-07-03 - src_alpha2: ar - tgt_alpha2: it - prefer_old: False - long_pair: ara-ita - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Nextcloud-AI/opus-mt-ar-fr	Nextcloud-AI	2023-08-16T11:25:41Z	104	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2024-02-23T10:37:21Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-ar-fr * source languages: ar * target languages: fr * OPUS readme: [ar-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/ar-fr/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-24.zip](https://object.pouta.csc.fi/OPUS-MT-models/ar-fr/opus-2020-01-24.zip) * test set translations: [opus-2020-01-24.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/ar-fr/opus-2020-01-24.test.txt) * test set scores: [opus-2020-01-24.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/ar-fr/opus-2020-01-24.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba.ar.fr \| 43.5 \| 0.602 \|
Nextcloud-AI/opus-mt-ar-es	Nextcloud-AI	2023-08-16T11:25:40Z	113	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "ar", "es", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2024-02-23T10:37:11Z	--- language: - ar - es tags: - translation license: apache-2.0 --- ### ara-spa * source group: Arabic * target group: Spanish * OPUS readme: [ara-spa](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ara-spa/README.md) * model: transformer * source language(s): apc apc_Latn ara arq * target language(s): spa * model: transformer * pre-processing: normalization + SentencePiece (spm32k,spm32k) * download original weights: [opus-2020-07-03.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/ara-spa/opus-2020-07-03.zip) * test set translations: [opus-2020-07-03.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/ara-spa/opus-2020-07-03.test.txt) * test set scores: [opus-2020-07-03.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/ara-spa/opus-2020-07-03.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.ara.spa \| 46.0 \| 0.641 \| ### System Info: - hf_name: ara-spa - source_languages: ara - target_languages: spa - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ara-spa/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['ar', 'es'] - src_constituents: {'apc', 'ara', 'arq_Latn', 'arq', 'afb', 'ara_Latn', 'apc_Latn', 'arz'} - tgt_constituents: {'spa'} - src_multilingual: False - tgt_multilingual: False - prepro: normalization + SentencePiece (spm32k,spm32k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/ara-spa/opus-2020-07-03.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/ara-spa/opus-2020-07-03.test.txt - src_alpha3: ara - tgt_alpha3: spa - short_pair: ar-es - chrF2_score: 0.6409999999999999 - bleu: 46.0 - brevity_penalty: 0.9620000000000001 - ref_len: 9708.0 - src_name: Arabic - tgt_name: Spanish - train_date: 2020-07-03 - src_alpha2: ar - tgt_alpha2: es - prefer_old: False - long_pair: ara-spa - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Helsinki-NLP/opus-mt-ar-eo	Helsinki-NLP	2023-08-16T11:25:37Z	132	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "ar", "eo", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- language: - ar - eo tags: - translation license: apache-2.0 --- ### ara-epo * source group: Arabic * target group: Esperanto * OPUS readme: [ara-epo](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ara-epo/README.md) * model: transformer-align * source language(s): apc apc_Latn ara arq arq_Latn arz * target language(s): epo * model: transformer-align * pre-processing: normalization + SentencePiece (spm4k,spm4k) * download original weights: [opus-2020-06-16.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/ara-epo/opus-2020-06-16.zip) * test set translations: [opus-2020-06-16.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/ara-epo/opus-2020-06-16.test.txt) * test set scores: [opus-2020-06-16.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/ara-epo/opus-2020-06-16.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.ara.epo \| 18.9 \| 0.376 \| ### System Info: - hf_name: ara-epo - source_languages: ara - target_languages: epo - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ara-epo/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['ar', 'eo'] - src_constituents: {'apc', 'ara', 'arq_Latn', 'arq', 'afb', 'ara_Latn', 'apc_Latn', 'arz'} - tgt_constituents: {'epo'} - src_multilingual: False - tgt_multilingual: False - prepro: normalization + SentencePiece (spm4k,spm4k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/ara-epo/opus-2020-06-16.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/ara-epo/opus-2020-06-16.test.txt - src_alpha3: ara - tgt_alpha3: epo - short_pair: ar-eo - chrF2_score: 0.376 - bleu: 18.9 - brevity_penalty: 0.948 - ref_len: 4506.0 - src_name: Arabic - tgt_name: Esperanto - train_date: 2020-06-16 - src_alpha2: ar - tgt_alpha2: eo - prefer_old: False - long_pair: ara-epo - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Nextcloud-AI/opus-mt-ar-de	Nextcloud-AI	2023-08-16T11:25:33Z	104	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "ar", "de", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2024-02-23T10:36:36Z	--- language: - ar - de tags: - translation license: apache-2.0 --- ### ara-deu * source group: Arabic * target group: German * OPUS readme: [ara-deu](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ara-deu/README.md) * model: transformer-align * source language(s): afb apc ara ara_Latn arq arz * target language(s): deu * model: transformer-align * pre-processing: normalization + SentencePiece (spm32k,spm32k) * download original weights: [opus-2020-07-03.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/ara-deu/opus-2020-07-03.zip) * test set translations: [opus-2020-07-03.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/ara-deu/opus-2020-07-03.test.txt) * test set scores: [opus-2020-07-03.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/ara-deu/opus-2020-07-03.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.ara.deu \| 44.7 \| 0.629 \| ### System Info: - hf_name: ara-deu - source_languages: ara - target_languages: deu - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ara-deu/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['ar', 'de'] - src_constituents: {'apc', 'ara', 'arq_Latn', 'arq', 'afb', 'ara_Latn', 'apc_Latn', 'arz'} - tgt_constituents: {'deu'} - src_multilingual: False - tgt_multilingual: False - prepro: normalization + SentencePiece (spm32k,spm32k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/ara-deu/opus-2020-07-03.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/ara-deu/opus-2020-07-03.test.txt - src_alpha3: ara - tgt_alpha3: deu - short_pair: ar-de - chrF2_score: 0.629 - bleu: 44.7 - brevity_penalty: 0.986 - ref_len: 8371.0 - src_name: Arabic - tgt_name: German - train_date: 2020-07-03 - src_alpha2: ar - tgt_alpha2: de - prefer_old: False - long_pair: ara-deu - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Helsinki-NLP/opus-mt-ar-de	Helsinki-NLP	2023-08-16T11:25:33Z	757	1	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "ar", "de", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- language: - ar - de tags: - translation license: apache-2.0 --- ### ara-deu * source group: Arabic * target group: German * OPUS readme: [ara-deu](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ara-deu/README.md) * model: transformer-align * source language(s): afb apc ara ara_Latn arq arz * target language(s): deu * model: transformer-align * pre-processing: normalization + SentencePiece (spm32k,spm32k) * download original weights: [opus-2020-07-03.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/ara-deu/opus-2020-07-03.zip) * test set translations: [opus-2020-07-03.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/ara-deu/opus-2020-07-03.test.txt) * test set scores: [opus-2020-07-03.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/ara-deu/opus-2020-07-03.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.ara.deu \| 44.7 \| 0.629 \| ### System Info: - hf_name: ara-deu - source_languages: ara - target_languages: deu - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/ara-deu/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['ar', 'de'] - src_constituents: {'apc', 'ara', 'arq_Latn', 'arq', 'afb', 'ara_Latn', 'apc_Latn', 'arz'} - tgt_constituents: {'deu'} - src_multilingual: False - tgt_multilingual: False - prepro: normalization + SentencePiece (spm32k,spm32k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/ara-deu/opus-2020-07-03.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/ara-deu/opus-2020-07-03.test.txt - src_alpha3: ara - tgt_alpha3: deu - short_pair: ar-de - chrF2_score: 0.629 - bleu: 44.7 - brevity_penalty: 0.986 - ref_len: 8371.0 - src_name: Arabic - tgt_name: German - train_date: 2020-07-03 - src_alpha2: ar - tgt_alpha2: de - prefer_old: False - long_pair: ara-deu - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Helsinki-NLP/opus-mt-am-sv	Helsinki-NLP	2023-08-16T11:25:32Z	122	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "am", "sv", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-am-sv * source languages: am * target languages: sv * OPUS readme: [am-sv](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/am-sv/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-08.zip](https://object.pouta.csc.fi/OPUS-MT-models/am-sv/opus-2020-01-08.zip) * test set translations: [opus-2020-01-08.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/am-sv/opus-2020-01-08.test.txt) * test set scores: [opus-2020-01-08.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/am-sv/opus-2020-01-08.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| JW300.am.sv \| 21.0 \| 0.377 \|
Helsinki-NLP/opus-mt-afa-en	Helsinki-NLP	2023-08-16T11:25:29Z	141	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "so", "ti", "am", "he", "mt", "ar", "afa", "en", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- language: - so - ti - am - he - mt - ar - afa - en tags: - translation license: apache-2.0 --- ### afa-eng * source group: Afro-Asiatic languages * target group: English * OPUS readme: [afa-eng](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/afa-eng/README.md) * model: transformer * source language(s): acm afb amh apc ara arq ary arz hau_Latn heb kab mlt rif_Latn shy_Latn som tir * target language(s): eng * model: transformer * pre-processing: normalization + SentencePiece (spm32k,spm32k) * download original weights: [opus2m-2020-07-31.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/afa-eng/opus2m-2020-07-31.zip) * test set translations: [opus2m-2020-07-31.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/afa-eng/opus2m-2020-07-31.test.txt) * test set scores: [opus2m-2020-07-31.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/afa-eng/opus2m-2020-07-31.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.amh-eng.amh.eng \| 35.9 \| 0.550 \| \| Tatoeba-test.ara-eng.ara.eng \| 36.6 \| 0.543 \| \| Tatoeba-test.hau-eng.hau.eng \| 11.9 \| 0.327 \| \| Tatoeba-test.heb-eng.heb.eng \| 42.7 \| 0.591 \| \| Tatoeba-test.kab-eng.kab.eng \| 4.3 \| 0.213 \| \| Tatoeba-test.mlt-eng.mlt.eng \| 44.3 \| 0.618 \| \| Tatoeba-test.multi.eng \| 27.1 \| 0.464 \| \| Tatoeba-test.rif-eng.rif.eng \| 3.5 \| 0.141 \| \| Tatoeba-test.shy-eng.shy.eng \| 0.6 \| 0.125 \| \| Tatoeba-test.som-eng.som.eng \| 23.6 \| 0.472 \| \| Tatoeba-test.tir-eng.tir.eng \| 13.1 \| 0.328 \| ### System Info: - hf_name: afa-eng - source_languages: afa - target_languages: eng - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/afa-eng/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['so', 'ti', 'am', 'he', 'mt', 'ar', 'afa', 'en'] - src_constituents: {'som', 'rif_Latn', 'tir', 'kab', 'arq', 'afb', 'amh', 'arz', 'heb', 'shy_Latn', 'apc', 'mlt', 'thv', 'ara', 'hau_Latn', 'acm', 'ary'} - tgt_constituents: {'eng'} - src_multilingual: True - tgt_multilingual: False - prepro: normalization + SentencePiece (spm32k,spm32k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/afa-eng/opus2m-2020-07-31.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/afa-eng/opus2m-2020-07-31.test.txt - src_alpha3: afa - tgt_alpha3: eng - short_pair: afa-en - chrF2_score: 0.46399999999999997 - bleu: 27.1 - brevity_penalty: 1.0 - ref_len: 69373.0 - src_name: Afro-Asiatic languages - tgt_name: English - train_date: 2020-07-31 - src_alpha2: afa - tgt_alpha2: en - prefer_old: False - long_pair: afa-eng - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Helsinki-NLP/opus-mt-af-sv	Helsinki-NLP	2023-08-16T11:25:27Z	116	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "af", "sv", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-af-sv * source languages: af * target languages: sv * OPUS readme: [af-sv](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/af-sv/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-08.zip](https://object.pouta.csc.fi/OPUS-MT-models/af-sv/opus-2020-01-08.zip) * test set translations: [opus-2020-01-08.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/af-sv/opus-2020-01-08.test.txt) * test set scores: [opus-2020-01-08.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/af-sv/opus-2020-01-08.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| JW300.af.sv \| 40.4 \| 0.599 \|
Helsinki-NLP/opus-mt-af-nl	Helsinki-NLP	2023-08-16T11:25:25Z	144	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "af", "nl", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- language: - af - nl tags: - translation license: apache-2.0 --- ### afr-nld * source group: Afrikaans * target group: Dutch * OPUS readme: [afr-nld](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/afr-nld/README.md) * model: transformer-align * source language(s): afr * target language(s): nld * model: transformer-align * pre-processing: normalization + SentencePiece (spm32k,spm32k) * download original weights: [opus-2020-06-17.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/afr-nld/opus-2020-06-17.zip) * test set translations: [opus-2020-06-17.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/afr-nld/opus-2020-06-17.test.txt) * test set scores: [opus-2020-06-17.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/afr-nld/opus-2020-06-17.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.afr.nld \| 55.2 \| 0.715 \| ### System Info: - hf_name: afr-nld - source_languages: afr - target_languages: nld - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/afr-nld/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['af', 'nl'] - src_constituents: {'afr'} - tgt_constituents: {'nld'} - src_multilingual: False - tgt_multilingual: False - prepro: normalization + SentencePiece (spm32k,spm32k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/afr-nld/opus-2020-06-17.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/afr-nld/opus-2020-06-17.test.txt - src_alpha3: afr - tgt_alpha3: nld - short_pair: af-nl - chrF2_score: 0.715 - bleu: 55.2 - brevity_penalty: 0.995 - ref_len: 6710.0 - src_name: Afrikaans - tgt_name: Dutch - train_date: 2020-06-17 - src_alpha2: af - tgt_alpha2: nl - prefer_old: False - long_pair: afr-nld - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Helsinki-NLP/opus-mt-af-fr	Helsinki-NLP	2023-08-16T11:25:24Z	129	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "af", "fr", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-af-fr * source languages: af * target languages: fr * OPUS readme: [af-fr](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/af-fr/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-08.zip](https://object.pouta.csc.fi/OPUS-MT-models/af-fr/opus-2020-01-08.zip) * test set translations: [opus-2020-01-08.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/af-fr/opus-2020-01-08.test.txt) * test set scores: [opus-2020-01-08.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/af-fr/opus-2020-01-08.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| JW300.af.fr \| 35.3 \| 0.543 \|
Helsinki-NLP/opus-mt-af-es	Helsinki-NLP	2023-08-16T11:25:22Z	123	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "af", "es", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- language: - af - es tags: - translation license: apache-2.0 --- ### afr-spa * source group: Afrikaans * target group: Spanish * OPUS readme: [afr-spa](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/afr-spa/README.md) * model: transformer-align * source language(s): afr * target language(s): spa * model: transformer-align * pre-processing: normalization + SentencePiece (spm32k,spm32k) * download original weights: [opus-2020-06-17.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/afr-spa/opus-2020-06-17.zip) * test set translations: [opus-2020-06-17.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/afr-spa/opus-2020-06-17.test.txt) * test set scores: [opus-2020-06-17.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/afr-spa/opus-2020-06-17.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba-test.afr.spa \| 49.9 \| 0.680 \| ### System Info: - hf_name: afr-spa - source_languages: afr - target_languages: spa - opus_readme_url: https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/afr-spa/README.md - original_repo: Tatoeba-Challenge - tags: ['translation'] - languages: ['af', 'es'] - src_constituents: {'afr'} - tgt_constituents: {'spa'} - src_multilingual: False - tgt_multilingual: False - prepro: normalization + SentencePiece (spm32k,spm32k) - url_model: https://object.pouta.csc.fi/Tatoeba-MT-models/afr-spa/opus-2020-06-17.zip - url_test_set: https://object.pouta.csc.fi/Tatoeba-MT-models/afr-spa/opus-2020-06-17.test.txt - src_alpha3: afr - tgt_alpha3: spa - short_pair: af-es - chrF2_score: 0.68 - bleu: 49.9 - brevity_penalty: 1.0 - ref_len: 2783.0 - src_name: Afrikaans - tgt_name: Spanish - train_date: 2020-06-17 - src_alpha2: af - tgt_alpha2: es - prefer_old: False - long_pair: afr-spa - helsinki_git_sha: 480fcbe0ee1bf4774bcbe6226ad9f58e63f6c535 - transformers_git_sha: 2207e5d8cb224e954a7cba69fa4ac2309e9ff30b - port_machine: brutasse - port_time: 2020-08-21-14:41
Helsinki-NLP/opus-mt-af-en	Helsinki-NLP	2023-08-16T11:25:20Z	4,596	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "af", "en", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-af-en * source languages: af * target languages: en * OPUS readme: [af-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/af-en/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2019-12-18.zip](https://object.pouta.csc.fi/OPUS-MT-models/af-en/opus-2019-12-18.zip) * test set translations: [opus-2019-12-18.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/af-en/opus-2019-12-18.test.txt) * test set scores: [opus-2019-12-18.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/af-en/opus-2019-12-18.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba.af.en \| 60.8 \| 0.736 \|
Helsinki-NLP/opus-mt-af-de	Helsinki-NLP	2023-08-16T11:25:19Z	150	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "af", "de", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-af-de * source languages: af * target languages: de * OPUS readme: [af-de](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/af-de/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-19.zip](https://object.pouta.csc.fi/OPUS-MT-models/af-de/opus-2020-01-19.zip) * test set translations: [opus-2020-01-19.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/af-de/opus-2020-01-19.test.txt) * test set scores: [opus-2020-01-19.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/af-de/opus-2020-01-19.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba.af.de \| 48.6 \| 0.681 \|
Helsinki-NLP/opus-mt-aed-es	Helsinki-NLP	2023-08-16T11:25:17Z	116	0	transformers	[ "transformers", "pytorch", "tf", "marian", "text2text-generation", "translation", "aed", "es", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-aed-es * source languages: aed * target languages: es * OPUS readme: [aed-es](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/aed-es/README.md) * dataset: opus * model: transformer-align * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-01-15.zip](https://object.pouta.csc.fi/OPUS-MT-models/aed-es/opus-2020-01-15.zip) * test set translations: [opus-2020-01-15.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/aed-es/opus-2020-01-15.test.txt) * test set scores: [opus-2020-01-15.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/aed-es/opus-2020-01-15.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| JW300.aed.es \| 89.1 \| 0.915 \|
Helsinki-NLP/opus-mt-ROMANCE-en	Helsinki-NLP	2023-08-16T11:25:14Z	88,075	8	transformers	[ "transformers", "pytorch", "tf", "rust", "marian", "text2text-generation", "translation", "roa", "en", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	translation	2022-03-02T23:29:04Z	--- tags: - translation license: apache-2.0 --- ### opus-mt-ROMANCE-en * source languages: fr,fr_BE,fr_CA,fr_FR,wa,frp,oc,ca,rm,lld,fur,lij,lmo,es,es_AR,es_CL,es_CO,es_CR,es_DO,es_EC,es_ES,es_GT,es_HN,es_MX,es_NI,es_PA,es_PE,es_PR,es_SV,es_UY,es_VE,pt,pt_br,pt_BR,pt_PT,gl,lad,an,mwl,it,it_IT,co,nap,scn,vec,sc,ro,la * target languages: en * OPUS readme: [fr+fr_BE+fr_CA+fr_FR+wa+frp+oc+ca+rm+lld+fur+lij+lmo+es+es_AR+es_CL+es_CO+es_CR+es_DO+es_EC+es_ES+es_GT+es_HN+es_MX+es_NI+es_PA+es_PE+es_PR+es_SV+es_UY+es_VE+pt+pt_br+pt_BR+pt_PT+gl+lad+an+mwl+it+it_IT+co+nap+scn+vec+sc+ro+la-en](https://github.com/Helsinki-NLP/OPUS-MT-train/blob/master/models/fr+fr_BE+fr_CA+fr_FR+wa+frp+oc+ca+rm+lld+fur+lij+lmo+es+es_AR+es_CL+es_CO+es_CR+es_DO+es_EC+es_ES+es_GT+es_HN+es_MX+es_NI+es_PA+es_PE+es_PR+es_SV+es_UY+es_VE+pt+pt_br+pt_BR+pt_PT+gl+lad+an+mwl+it+it_IT+co+nap+scn+vec+sc+ro+la-en/README.md) * dataset: opus * model: transformer * pre-processing: normalization + SentencePiece * download original weights: [opus-2020-04-01.zip](https://object.pouta.csc.fi/OPUS-MT-models/fr+fr_BE+fr_CA+fr_FR+wa+frp+oc+ca+rm+lld+fur+lij+lmo+es+es_AR+es_CL+es_CO+es_CR+es_DO+es_EC+es_ES+es_GT+es_HN+es_MX+es_NI+es_PA+es_PE+es_PR+es_SV+es_UY+es_VE+pt+pt_br+pt_BR+pt_PT+gl+lad+an+mwl+it+it_IT+co+nap+scn+vec+sc+ro+la-en/opus-2020-04-01.zip) * test set translations: [opus-2020-04-01.test.txt](https://object.pouta.csc.fi/OPUS-MT-models/fr+fr_BE+fr_CA+fr_FR+wa+frp+oc+ca+rm+lld+fur+lij+lmo+es+es_AR+es_CL+es_CO+es_CR+es_DO+es_EC+es_ES+es_GT+es_HN+es_MX+es_NI+es_PA+es_PE+es_PR+es_SV+es_UY+es_VE+pt+pt_br+pt_BR+pt_PT+gl+lad+an+mwl+it+it_IT+co+nap+scn+vec+sc+ro+la-en/opus-2020-04-01.test.txt) * test set scores: [opus-2020-04-01.eval.txt](https://object.pouta.csc.fi/OPUS-MT-models/fr+fr_BE+fr_CA+fr_FR+wa+frp+oc+ca+rm+lld+fur+lij+lmo+es+es_AR+es_CL+es_CO+es_CR+es_DO+es_EC+es_ES+es_GT+es_HN+es_MX+es_NI+es_PA+es_PE+es_PR+es_SV+es_UY+es_VE+pt+pt_br+pt_BR+pt_PT+gl+lad+an+mwl+it+it_IT+co+nap+scn+vec+sc+ro+la-en/opus-2020-04-01.eval.txt) ## Benchmarks \| testset \| BLEU \| chr-F \| \|-----------------------\|-------\|-------\| \| Tatoeba.fr.en \| 62.2 \| 0.750 \|
Hansaht/Text_classification_model_1_pytorch	Hansaht	2023-08-16T11:22:15Z	118	1	transformers	[ "transformers", "pytorch", "tensorboard", "safetensors", "distilbert", "text-classification", "generated_from_trainer", "en", "dataset:imdb", "base_model:distilbert/distilbert-base-uncased", "base_model:finetune:distilbert/distilbert-base-uncased", "license:apache-2.0", "model-index", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2023-07-20T08:51:58Z	--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_trainer datasets: - imdb metrics: - accuracy model-index: - name: Text_classification_model_1_pytorch results: - task: name: Text Classification type: text-classification dataset: name: imdb type: imdb config: plain_text split: test args: plain_text metrics: - name: Accuracy type: accuracy value: 0.93292 language: - en --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # Text_classification_model_1_pytorch This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the imdb dataset. It achieves the following results on the evaluation set: - Loss: 0.3494 - Accuracy: 0.9329 ## Model description Introduction: In the realm of natural language processing and sentiment analysis, the utilization of pre-trained language models has proven to be highly effective. One such model is DistilBERT Uncased, a distilled and smaller version of the powerful BERT model. In this project, we explore the application of DistilBERT Uncased for text classification, specifically focusing on sentiment analysis using the IMDb dataset. Model Overview: Our text classification model is built upon the foundation of DistilBERT Uncased. This model, developed by Hugging Face, is a variant of BERT that retains much of BERT's effectiveness while being lighter and faster. DistilBERT retains the bidirectional attention mechanism and the masked language model pre-training objective of BERT. Our aim is to fine-tune this pre-trained model to accurately predict the sentiment of movie reviews as either positive or negative. ## Intended uses & limitations we've demonstrated the effectiveness of fine-tuning DistilBERT Uncased for text classification, specifically for sentiment analysis using the IMDb dataset. Our model showcases the power of transfer learning, allowing it to leverage pre-trained knowledge and adapt it to a specific task. The fine-tuned model can accurately classify movie reviews as positive or negative, paving the way for efficient sentiment analysis in various applications. ## Training and evaluation data Dataset: The IMDb dataset, a widely-used benchmark for sentiment analysis, consists of movie reviews labeled as positive or negative based on their sentiment. This dataset encompasses a wide range of reviews from IMDb, offering a diverse set of language patterns, tones, and opinions. By training our model on this dataset, we aim to enable it to learn the nuances of positive and negative sentiment expression. ## Training procedure ### Fine-Tuning Process: Fine-tuning the DistilBERT Uncased model for sentiment analysis involves adapting the pre-trained model to our specific task. This process entails: Data Preprocessing: The IMDb dataset is preprocessed, tokenized, and encoded into input features that DistilBERT Uncased can understand. These features include tokenized text and segment IDs, which differentiate between the actual text and padding tokens. Fine-Tuning Architecture: We attach a classification layer on top of DistilBERT's transformer layers. This additional layer learns to map the contextualized embeddings generated by DistilBERT to sentiment labels (positive or negative). Training: The model is trained using the training subset of the IMDb dataset. During training, the classification layer's weights are updated based on the model's predictions and the ground truth labels. We use cross-entropy loss as the optimization objective. Validation: The model's performance is evaluated on a separate validation subset of the IMDb dataset. This helps us monitor its learning progress and make adjustments if needed. ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:--------:\| \| 0.2336 \| 1.0 \| 1563 \| 0.2718 \| 0.903 \| \| 0.162 \| 2.0 \| 3126 \| 0.2392 \| 0.9277 \| \| 0.0971 \| 3.0 \| 4689 \| 0.3191 \| 0.9312 \| \| 0.0535 \| 4.0 \| 6252 \| 0.3211 \| 0.9334 \| \| 0.034 \| 5.0 \| 7815 \| 0.3494 \| 0.9329 \| ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.13.1 - Tokenizers 0.13.3
Vertti/TuumaPEFTExperiment	Vertti	2023-08-16T11:01:41Z	0	0	null	[ "region:us" ]	null	2023-08-16T08:11:40Z	### A completely useless adapter trained on nothing. --- library_name: peft --- ## Training procedure ### Framework versions - PEFT 0.5.0.dev0
mindreader/llama-recipe-7b-1epoch-8batch	mindreader	2023-08-16T10:52:06Z	4	0	peft	[ "peft", "pytorch", "llama", "region:us" ]	null	2023-08-15T06:37:14Z	--- library_name: peft --- !python llama-recipes/llama_finetuning.py \ --use_peft \ --num_epochs 1 \ --peft_method lora \ --run_validation false \ --quantization \ --dataset alpaca_dataset \ --model_name meta-llama/Llama-2-7b-chat-hf \ --save_model \ --save_optimizer \ --batch_size_training 8 \ --output_dir ./save ## Training procedure The following `bitsandbytes` quantization config was used during training: - load_in_8bit: True - load_in_4bit: False - llm_int8_threshold: 6.0 - llm_int8_skip_modules: None - llm_int8_enable_fp32_cpu_offload: False - llm_int8_has_fp16_weight: False - bnb_4bit_quant_type: fp4 - bnb_4bit_use_double_quant: False - bnb_4bit_compute_dtype: float32 ### Framework versions - PEFT 0.5.0.dev0
bhushan4401/xyz	bhushan4401	2023-08-16T10:45:48Z	61	0	transformers	[ "transformers", "tf", "distilbert", "text-classification", "generated_from_keras_callback", "base_model:distilbert/distilbert-base-uncased", "base_model:finetune:distilbert/distilbert-base-uncased", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2023-08-16T10:33:43Z	--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_keras_callback model-index: - name: bhushan4401/xyz results: [] --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # bhushan4401/xyz This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset. It achieves the following results on the evaluation set: - Train Loss: 0.5297 - Validation Loss: 0.2912 - Train Accuracy: 1.0 - Epoch: 0 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': False, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 7810, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False} - training_precision: float32 ### Training results \| Train Loss \| Validation Loss \| Train Accuracy \| Epoch \| \|:----------:\|:---------------:\|:--------------:\|:-----:\| \| 0.5297 \| 0.2912 \| 1.0 \| 0 \| ### Framework versions - Transformers 4.31.0 - TensorFlow 2.12.0 - Datasets 2.14.4 - Tokenizers 0.13.3
ELggman/distilbert-base-uncased-finetuned-imdb	ELggman	2023-08-16T10:34:54Z	115	0	transformers	[ "transformers", "pytorch", "tensorboard", "distilbert", "fill-mask", "generated_from_trainer", "dataset:imdb", "base_model:distilbert/distilbert-base-uncased", "base_model:finetune:distilbert/distilbert-base-uncased", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	fill-mask	2023-08-16T10:29:46Z	--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_trainer datasets: - imdb model-index: - name: distilbert-base-uncased-finetuned-imdb results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # distilbert-base-uncased-finetuned-imdb This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the imdb dataset. It achieves the following results on the evaluation set: - Loss: 2.4252 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3.0 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| \|:-------------:\|:-----:\|:----:\|:---------------:\| \| 2.6961 \| 1.0 \| 157 \| 2.5442 \| \| 2.5696 \| 2.0 \| 314 \| 2.4639 \| \| 2.5438 \| 3.0 \| 471 \| 2.4252 \| ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3
CyberHarem/hestia_isitwrongtotrytopickupgirlsinadungeon	CyberHarem	2023-08-16T10:21:29Z	0	1	null	[ "art", "text-to-image", "dataset:CyberHarem/hestia_isitwrongtotrytopickupgirlsinadungeon", "license:mit", "region:us" ]	text-to-image	2023-08-16T10:15:43Z	--- license: mit datasets: - CyberHarem/hestia_isitwrongtotrytopickupgirlsinadungeon pipeline_tag: text-to-image tags: - art --- # Lora of hestia_isitwrongtotrytopickupgirlsinadungeon This model is trained with [HCP-Diffusion](https://github.com/7eu7d7/HCP-Diffusion). And the auto-training framework is maintained by [DeepGHS Team](https://huggingface.co/deepghs). After downloading the pt and safetensors files for the specified step, you need to use them simultaneously. The pt file will be used as an embedding, while the safetensors file will be loaded for Lora. For example, if you want to use the model from step 1500, you need to download `1500/hestia_isitwrongtotrytopickupgirlsinadungeon.pt` as the embedding and `1500/hestia_isitwrongtotrytopickupgirlsinadungeon.safetensors` for loading Lora. By using both files together, you can generate images for the desired characters. The trigger word is `hestia_isitwrongtotrytopickupgirlsinadungeon`. These are available steps: \| Steps \| pattern_1 \| pattern_2 \| bikini \| free \| nude \| Download \| \|--------:\|:-----------------------------------------------\|:-----------------------------------------------\|:-----------------------------------------\|:-------------------------------------\|:-----------------------------------------------\|:------------------------------------------------------------------\| \| 1500 \| ![pattern_1-1500](1500/previews/pattern_1.png) \| ![pattern_2-1500](1500/previews/pattern_2.png) \| ![bikini-1500](1500/previews/bikini.png) \| ![free-1500](1500/previews/free.png) \| [<NSFW, click to see>](1500/previews/nude.png) \| [Download](1500/hestia_isitwrongtotrytopickupgirlsinadungeon.zip) \| \| 1400 \| ![pattern_1-1400](1400/previews/pattern_1.png) \| ![pattern_2-1400](1400/previews/pattern_2.png) \| ![bikini-1400](1400/previews/bikini.png) \| ![free-1400](1400/previews/free.png) \| [<NSFW, click to see>](1400/previews/nude.png) \| [Download](1400/hestia_isitwrongtotrytopickupgirlsinadungeon.zip) \| \| 1300 \| ![pattern_1-1300](1300/previews/pattern_1.png) \| ![pattern_2-1300](1300/previews/pattern_2.png) \| ![bikini-1300](1300/previews/bikini.png) \| ![free-1300](1300/previews/free.png) \| [<NSFW, click to see>](1300/previews/nude.png) \| [Download](1300/hestia_isitwrongtotrytopickupgirlsinadungeon.zip) \| \| 1200 \| ![pattern_1-1200](1200/previews/pattern_1.png) \| ![pattern_2-1200](1200/previews/pattern_2.png) \| ![bikini-1200](1200/previews/bikini.png) \| ![free-1200](1200/previews/free.png) \| [<NSFW, click to see>](1200/previews/nude.png) \| [Download](1200/hestia_isitwrongtotrytopickupgirlsinadungeon.zip) \| \| 1100 \| ![pattern_1-1100](1100/previews/pattern_1.png) \| ![pattern_2-1100](1100/previews/pattern_2.png) \| ![bikini-1100](1100/previews/bikini.png) \| ![free-1100](1100/previews/free.png) \| [<NSFW, click to see>](1100/previews/nude.png) \| [Download](1100/hestia_isitwrongtotrytopickupgirlsinadungeon.zip) \| \| 1000 \| ![pattern_1-1000](1000/previews/pattern_1.png) \| ![pattern_2-1000](1000/previews/pattern_2.png) \| ![bikini-1000](1000/previews/bikini.png) \| ![free-1000](1000/previews/free.png) \| [<NSFW, click to see>](1000/previews/nude.png) \| [Download](1000/hestia_isitwrongtotrytopickupgirlsinadungeon.zip) \| \| 900 \| ![pattern_1-900](900/previews/pattern_1.png) \| ![pattern_2-900](900/previews/pattern_2.png) \| ![bikini-900](900/previews/bikini.png) \| ![free-900](900/previews/free.png) \| [<NSFW, click to see>](900/previews/nude.png) \| [Download](900/hestia_isitwrongtotrytopickupgirlsinadungeon.zip) \| \| 800 \| ![pattern_1-800](800/previews/pattern_1.png) \| ![pattern_2-800](800/previews/pattern_2.png) \| ![bikini-800](800/previews/bikini.png) \| ![free-800](800/previews/free.png) \| [<NSFW, click to see>](800/previews/nude.png) \| [Download](800/hestia_isitwrongtotrytopickupgirlsinadungeon.zip) \| \| 700 \| ![pattern_1-700](700/previews/pattern_1.png) \| ![pattern_2-700](700/previews/pattern_2.png) \| ![bikini-700](700/previews/bikini.png) \| ![free-700](700/previews/free.png) \| [<NSFW, click to see>](700/previews/nude.png) \| [Download](700/hestia_isitwrongtotrytopickupgirlsinadungeon.zip) \| \| 600 \| ![pattern_1-600](600/previews/pattern_1.png) \| ![pattern_2-600](600/previews/pattern_2.png) \| ![bikini-600](600/previews/bikini.png) \| ![free-600](600/previews/free.png) \| [<NSFW, click to see>](600/previews/nude.png) \| [Download](600/hestia_isitwrongtotrytopickupgirlsinadungeon.zip) \| \| 500 \| ![pattern_1-500](500/previews/pattern_1.png) \| ![pattern_2-500](500/previews/pattern_2.png) \| ![bikini-500](500/previews/bikini.png) \| ![free-500](500/previews/free.png) \| [<NSFW, click to see>](500/previews/nude.png) \| [Download](500/hestia_isitwrongtotrytopickupgirlsinadungeon.zip) \| \| 400 \| ![pattern_1-400](400/previews/pattern_1.png) \| ![pattern_2-400](400/previews/pattern_2.png) \| ![bikini-400](400/previews/bikini.png) \| ![free-400](400/previews/free.png) \| [<NSFW, click to see>](400/previews/nude.png) \| [Download](400/hestia_isitwrongtotrytopickupgirlsinadungeon.zip) \| \| 300 \| ![pattern_1-300](300/previews/pattern_1.png) \| ![pattern_2-300](300/previews/pattern_2.png) \| ![bikini-300](300/previews/bikini.png) \| ![free-300](300/previews/free.png) \| [<NSFW, click to see>](300/previews/nude.png) \| [Download](300/hestia_isitwrongtotrytopickupgirlsinadungeon.zip) \| \| 200 \| ![pattern_1-200](200/previews/pattern_1.png) \| ![pattern_2-200](200/previews/pattern_2.png) \| ![bikini-200](200/previews/bikini.png) \| ![free-200](200/previews/free.png) \| [<NSFW, click to see>](200/previews/nude.png) \| [Download](200/hestia_isitwrongtotrytopickupgirlsinadungeon.zip) \| \| 100 \| ![pattern_1-100](100/previews/pattern_1.png) \| ![pattern_2-100](100/previews/pattern_2.png) \| ![bikini-100](100/previews/bikini.png) \| ![free-100](100/previews/free.png) \| [<NSFW, click to see>](100/previews/nude.png) \| [Download](100/hestia_isitwrongtotrytopickupgirlsinadungeon.zip) \|
toastyfrosty/controlearth-sct	toastyfrosty	2023-08-16T10:20:34Z	4	0	diffusers	[ "diffusers", "license:apache-2.0", "region:us" ]	null	2023-08-14T06:59:31Z	--- license: apache-2.0 --- (Note that this model is for comparison purposes only. A better performing model can be found [here](https://huggingface.co/tostyfrosty/controlearth).) # Model description ControlNet model conditioned on OpenStreetMaps (OSM) to generate the corresponding satellite images. Trained on the region of Scotland. To access the better performing model* trained on the WorldImagery Clarity dataset, see [this model](https://huggingface.co/tostyfrosty/controlearth).* ## Dataset used for training The dataset used for the training procedure is the [WorldImagery dataset](https://www.arcgis.com/home/item.html?id=10df2279f9684e4a9f6a7f08febac2a9). This dataset is qualitatively worse than its predecessor [WorldImagery Clarity dataset](https://www.arcgis.com/home/item.html?id=ab399b847323487dba26809bf11ea91a). The code for the dataset construction can be accessed in https://github.com/tostyfrosty/map-sat. ![examples image](https://raw.githubusercontent.com/tostyfrosty/map-sat/main/imgs/examples-controlnet-sct.png)
AptaArkana/indonesian_toxic_classification	AptaArkana	2023-08-16T10:20:10Z	103	0	transformers	[ "transformers", "pytorch", "tensorboard", "bert", "text-classification", "generated_from_trainer", "license:apache-2.0", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2023-08-16T07:58:01Z	--- license: apache-2.0 tags: - generated_from_trainer metrics: - accuracy - precision - recall - f1 model-index: - name: kata_kasar_test results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # kata_kasar_test This model is a fine-tuned version of [indolem/indobertweet-base-uncased](https://huggingface.co/indolem/indobertweet-base-uncased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0099 - Accuracy: 0.9963 - Precision: 0.9926 - Recall: 1.0 - F1: 0.9963 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 2 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \| Precision \| Recall \| F1 \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:--------:\|:---------:\|:------:\|:------:\| \| 0.053 \| 1.0 \| 547 \| 0.0215 \| 0.9963 \| 0.9944 \| 0.9981 \| 0.9963 \| \| 0.0043 \| 2.0 \| 1094 \| 0.0099 \| 0.9963 \| 0.9926 \| 1.0 \| 0.9963 \| ### Framework versions - Transformers 4.26.1 - Pytorch 1.13.1+cpu - Datasets 2.11.0 - Tokenizers 0.13.2
dantepalacio/ruLongT5-Large	dantepalacio	2023-08-16T10:13:07Z	80	0	transformers	[ "transformers", "pytorch", "longt5", "text2text-generation", "ru", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text2text-generation	2023-08-14T08:56:57Z	--- language: - ru --- original model: agemagician/mlong-t5-tglobal-large adaptation guide: https://towardsdatascience.com/how-to-adapt-a-multilingual-t5-model-for-a-single-language-b9f94f3d9c90 import torch from transformers import MT5Tokenizer, LongT5ForConditionalGeneration model_name = "dantepalacio/ruLongT5-Large" tokenizer = MT5Tokenizer.from_pretrained(model_name) model = LongT5ForConditionalGeneration.from_pretrained(model_name, ignore_mismatched_sizes=True)
DrasticActions/gok-so-vits-svc-models	DrasticActions	2023-08-16T10:11:14Z	0	0	null	[ "license:cc", "region:us" ]	null	2023-08-15T12:54:36Z	--- license: cc --- # GOK so-vits-svc models ## How to use - Install https://github.com/voicepaw/so-vits-svc-fork - [Download the models](https://huggingface.co/DrasticActions/gok-so-vits-svc-models/tree/main/Models) from this repo - Open the svc GUI - Under Paths, set the model path to the specific "G_*.pth" file you want to use. - Set the config path to the config.json from the same model path folder. - The Input Audio should only be a (single) speaker's voice. For that, you can use https://ultimatevocalremover.com/ - To create the file, click "Infer"
manuu01/xtremedistil-l6-h256-uncased-nli	manuu01	2023-08-16T10:09:36Z	69	0	transformers	[ "transformers", "tf", "bert", "text-classification", "generated_from_keras_callback", "dataset:scitail", "dataset:multi_nli", "dataset:anli", "dataset:snli", "dataset:bias-amplified-splits/wanli", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2023-08-13T21:37:40Z	--- tags: - generated_from_keras_callback model-index: - name: xtremedistil-l6-h256-uncased-nli results: [] datasets: - scitail - multi_nli - anli - snli - bias-amplified-splits/wanli --- <!-- This model card has been generated automatically according to the information Keras had access to. You should probably proofread and complete it, then remove this comment. --> # xtremedistil-l6-h256-uncased-nli The model base is [xtremedistil-l6-h256-uncased](https://huggingface.co/microsoft/xtremedistil-l6-h256-uncased). It has been fine-tuned on: [snli](https://huggingface.co/datasets/snli), [wanli](https://huggingface.co/datasets/alisawuffles/WANLI), [mnli](https://huggingface.co/datasets/multi_nli), [anli](https://huggingface.co/datasets/anli), [scitail](https://huggingface.co/datasets/scitail) ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters ### Training results It achieved the following accuracy during training (on validation sets): SNLI: 87.90% MNLI: 82.27% ANLI_r3: 44.83% scitail: 91.02% ### Framework versions - Transformers 4.31.0 - TensorFlow 2.12.0 - Datasets 2.14.4 - Tokenizers 0.13.3
maroti/q-taxiv3	maroti	2023-08-16T09:54:03Z	0	0	null	[ "Taxi-v3", "q-learning", "reinforcement-learning", "custom-implementation", "model-index", "region:us" ]	reinforcement-learning	2023-08-16T09:54:01Z	--- tags: - Taxi-v3 - q-learning - reinforcement-learning - custom-implementation model-index: - name: q-taxiv3 results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: Taxi-v3 type: Taxi-v3 metrics: - type: mean_reward value: 7.48 +/- 2.78 name: mean_reward verified: false --- # Q-Learning Agent playing1 Taxi-v3 This is a trained model of a Q-Learning agent playing Taxi-v3 . ## Usage ```python model = load_from_hub(repo_id="maroti/q-taxiv3", filename="q-learning.pkl") # Don't forget to check if you need to add additional attributes (is_slippery=False etc) env = gym.make(model["env_id"]) ```
ailabturkiye/epha	ailabturkiye	2023-08-16T09:52:45Z	0	0	null	[ "music", "tr", "license:openrail", "region:us" ]	null	2023-08-16T09:48:53Z	--- license: openrail language: - tr tags: - music --- Epha'nın videosunun sesiyle oluşturulan ses modeli. Train benim tarafımdan yapılmıştır.
maroti/q-FrozenLake-v1-4x4-noSlippery	maroti	2023-08-16T09:51:38Z	0	0	null	[ "FrozenLake-v1-4x4-no_slippery", "q-learning", "reinforcement-learning", "custom-implementation", "model-index", "region:us" ]	reinforcement-learning	2023-08-16T09:51:35Z	--- tags: - FrozenLake-v1-4x4-no_slippery - q-learning - reinforcement-learning - custom-implementation model-index: - name: q-FrozenLake-v1-4x4-noSlippery results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: FrozenLake-v1-4x4-no_slippery type: FrozenLake-v1-4x4-no_slippery metrics: - type: mean_reward value: 1.00 +/- 0.00 name: mean_reward verified: false --- # Q-Learning Agent playing1 FrozenLake-v1 This is a trained model of a Q-Learning agent playing FrozenLake-v1 . ## Usage ```python model = load_from_hub(repo_id="maroti/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl") # Don't forget to check if you need to add additional attributes (is_slippery=False etc) env = gym.make(model["env_id"]) ```
huangyuyang/Qwen-7B-Chat-int8.flm	huangyuyang	2023-08-16T09:51:01Z	0	4	null	[ "license:apache-2.0", "region:us" ]	null	2023-08-16T09:06:35Z	--- license: apache-2.0 --- fastllm model for Qwen-7B-Chat-int8 Github address: https://github.com/ztxz16/fastllm
qgallouedec/tqc-PandaReach-v1-2232459529	qgallouedec	2023-08-16T09:43:21Z	5	0	stable-baselines3	[ "stable-baselines3", "PandaReach-v1", "deep-reinforcement-learning", "reinforcement-learning", "arxiv:2106.13687", "model-index", "region:us" ]	reinforcement-learning	2023-02-27T15:36:34Z	--- library_name: stable-baselines3 tags: - PandaReach-v1 - deep-reinforcement-learning - reinforcement-learning - stable-baselines3 model-index: - name: TQC results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: PandaReach-v1 type: PandaReach-v1 metrics: - type: mean_reward value: -2.20 +/- 0.75 name: mean_reward verified: false --- # TQC Agent playing PandaReach-v1 This is a trained model of a TQC agent playing PandaReach-v1 (arxiv.org/abs/2106.13687) using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3) and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo). The RL Zoo is a training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included. ## Usage (with SB3 RL Zoo) RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/> SB3: https://github.com/DLR-RM/stable-baselines3<br/> SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib Install the RL Zoo (with SB3 and SB3-Contrib): ```bash pip install rl_zoo3 ``` ``` # Download model and save it into the logs/ folder python -m rl_zoo3.load_from_hub --algo tqc --env PandaReach-v1 -orga qgallouedec -f logs/ python -m rl_zoo3.enjoy --algo tqc --env PandaReach-v1 -f logs/ ``` If you installed the RL Zoo3 via pip (`pip install rl_zoo3`), from anywhere you can do: ``` python -m rl_zoo3.load_from_hub --algo tqc --env PandaReach-v1 -orga qgallouedec -f logs/ python -m rl_zoo3.enjoy --algo tqc --env PandaReach-v1 -f logs/ ``` ## Training (with the RL Zoo) ``` python -m rl_zoo3.train --algo tqc --env PandaReach-v1 -f logs/ # Upload the model and generate video (when possible) python -m rl_zoo3.push_to_hub --algo tqc --env PandaReach-v1 -f logs/ -orga qgallouedec ``` ## Hyperparameters ```python OrderedDict([('batch_size', 256), ('buffer_size', 1000000), ('ent_coef', 'auto'), ('env_wrapper', 'sb3_contrib.common.wrappers.TimeFeatureWrapper'), ('gamma', 0.95), ('learning_rate', 0.001), ('learning_starts', 1000), ('n_timesteps', 20000.0), ('normalize', True), ('policy', 'MultiInputPolicy'), ('policy_kwargs', 'dict(net_arch=[64, 64], n_critics=1)'), ('replay_buffer_class', 'HerReplayBuffer'), ('replay_buffer_kwargs', "dict( online_sampling=True, goal_selection_strategy='future', " 'n_sampled_goal=4 )'), ('normalize_kwargs', {'norm_obs': True, 'norm_reward': False})]) ``` # Environment Arguments ```python {'render': True} ```
AXX1995/homarekittenv1	AXX1995	2023-08-16T09:35:21Z	0	0	null	[ "license:creativeml-openrail-m", "region:us" ]	null	2023-08-16T09:10:48Z	--- license: creativeml-openrail-m ---
PhysHunter/whisper-tiny-en	PhysHunter	2023-08-16T09:16:59Z	85	0	transformers	[ "transformers", "pytorch", "tensorboard", "whisper", "automatic-speech-recognition", "generated_from_trainer", "dataset:PolyAI/minds14", "base_model:openai/whisper-tiny", "base_model:finetune:openai/whisper-tiny", "license:apache-2.0", "model-index", "endpoints_compatible", "region:us" ]	automatic-speech-recognition	2023-08-16T08:05:42Z	--- license: apache-2.0 base_model: openai/whisper-tiny tags: - generated_from_trainer datasets: - PolyAI/minds14 metrics: - wer model-index: - name: whisper-tiny-en results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: PolyAI/minds14 type: PolyAI/minds14 config: en-US split: train args: en-US metrics: - name: Wer type: wer value: 0.3020257826887661 --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # whisper-tiny-en This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set: - Loss: 0.5262 - Wer Ortho: 0.3119 - Wer: 0.3020 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 20 - training_steps: 200 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Wer Ortho \| Wer \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:---------:\|:------:\| \| 0.4823 \| 3.57 \| 50 \| 0.5315 \| 0.3202 \| 0.3088 \| \| 0.1361 \| 7.14 \| 100 \| 0.4843 \| 0.3253 \| 0.3161 \| \| 0.0563 \| 10.71 \| 150 \| 0.5113 \| 0.3106 \| 0.3020 \| \| 0.0374 \| 14.29 \| 200 \| 0.5262 \| 0.3119 \| 0.3020 \| ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3
fp16-guy/YesMix_2.0_fp16_cleaned	fp16-guy	2023-08-16T09:12:55Z	0	1	null	[ "text-to-image", "region:us" ]	text-to-image	2023-08-05T09:17:35Z	--- pipeline_tag: text-to-image --- 【Checkpoint】YesMix, but fp16/cleaned - smaller size, same result. ======== /// [original checkpoint link](https://civitai.com/models/9139/checkpointyesmix) (all rights to the model belong to zakp) --- [grid 01](https://huggingface.co/datasets/fp16-guy/grids/blob/main/yesmix%2020%2001%2020230805110225-111-CheckpointYesmix_v20-Euler%20a-6.png) (1.99gb version)* [grid 02](https://huggingface.co/datasets/fp16-guy/grids/blob/main/yesmix%2020%2002%2020230805110340-111-CheckpointYesmix_v20-Euler%20a-6.png) (1.83gb version - no vae)* [grid 03](https://huggingface.co/datasets/fp16-guy/grids_inp/blob/main/CheckpointYesmix_v20%20inp%2001%2020230815215238-111-CheckpointYesmix_v20_fp16-Euler%20a-5.5.png) (1.99gb inpainting version)* [grid 04](https://huggingface.co/datasets/fp16-guy/grids_inp/blob/main/CheckpointYesmix_v20%20inp%2002%2020230816120951-111-CheckpointYesmix_v20_fp16_no_vae-Euler%20a-5.5.png) (1.83gb inpainting version - no vae)*
Old-Shatterhand/esm_fine_fluorescence	Old-Shatterhand	2023-08-16T09:08:34Z	108	0	transformers	[ "transformers", "pytorch", "tensorboard", "esm", "text-classification", "protein", "classification", "fluorescence", "en", "dataset:proteinea/fluorescence", "license:mit", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2023-08-12T06:24:24Z	--- license: mit datasets: - proteinea/fluorescence language: - en metrics: - accuracy library_name: transformers pipeline_tag: text-classification tags: - protein - esm - classification - fluorescence ---
huangyuyang/Qwen-7B-Chat-int4.flm	huangyuyang	2023-08-16T09:04:11Z	0	3	null	[ "license:apache-2.0", "region:us" ]	null	2023-08-16T08:08:01Z	--- license: apache-2.0 --- fastllm model for Qweb-7B-Chat-int4 Github address: https://github.com/ztxz16/fastllm
harshit989/my_awesome_billsum_model	harshit989	2023-08-16T08:59:17Z	103	0	transformers	[ "transformers", "pytorch", "tensorboard", "t5", "text2text-generation", "generated_from_trainer", "dataset:billsum", "base_model:google-t5/t5-small", "base_model:finetune:google-t5/t5-small", "license:apache-2.0", "model-index", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text2text-generation	2023-08-16T08:33:35Z	--- license: apache-2.0 base_model: t5-small tags: - generated_from_trainer datasets: - billsum metrics: - rouge model-index: - name: my_awesome_billsum_model results: - task: name: Sequence-to-sequence Language Modeling type: text2text-generation dataset: name: billsum type: billsum config: default split: ca_test args: default metrics: - name: Rouge1 type: rouge value: 0.1416 --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # my_awesome_billsum_model This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the billsum dataset. It achieves the following results on the evaluation set: - Loss: 2.4956 - Rouge1: 0.1416 - Rouge2: 0.0491 - Rougel: 0.1176 - Rougelsum: 0.1175 - Gen Len: 19.0 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 4 ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Rouge1 \| Rouge2 \| Rougel \| Rougelsum \| Gen Len \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:------:\|:------:\|:------:\|:---------:\|:-------:\| \| No log \| 1.0 \| 62 \| 2.7923 \| 0.1292 \| 0.0404 \| 0.1095 \| 0.1094 \| 19.0 \| \| No log \| 2.0 \| 124 \| 2.5788 \| 0.1378 \| 0.0491 \| 0.1166 \| 0.1165 \| 19.0 \| \| No log \| 3.0 \| 186 \| 2.5125 \| 0.1409 \| 0.0486 \| 0.1174 \| 0.1172 \| 19.0 \| \| No log \| 4.0 \| 248 \| 2.4956 \| 0.1416 \| 0.0491 \| 0.1176 \| 0.1175 \| 19.0 \| ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3
phatpt/q-FrozenLake-v1-4x4-noSlippery	phatpt	2023-08-16T08:30:59Z	0	0	null	[ "FrozenLake-v1-4x4-no_slippery", "q-learning", "reinforcement-learning", "custom-implementation", "model-index", "region:us" ]	reinforcement-learning	2023-08-16T08:30:00Z	--- tags: - FrozenLake-v1-4x4-no_slippery - q-learning - reinforcement-learning - custom-implementation model-index: - name: q-FrozenLake-v1-4x4-noSlippery results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: FrozenLake-v1-4x4-no_slippery type: FrozenLake-v1-4x4-no_slippery metrics: - type: mean_reward value: 1.00 +/- 0.00 name: mean_reward verified: false --- # Q-Learning Agent playing1 FrozenLake-v1 This is a trained model of a Q-Learning agent playing FrozenLake-v1 . ## Usage ```python model = load_from_hub(repo_id="phatpt/q-FrozenLake-v1-4x4-noSlippery", filename="q-learning.pkl") # Don't forget to check if you need to add additional attributes (is_slippery=False etc) env = gym.make(model["env_id"]) ```
linoyts/lora-trained-xl-colab-woman-5e-06-1000	linoyts	2023-08-16T08:30:30Z	0	1	diffusers	[ "diffusers", "stable-diffusion-xl", "stable-diffusion-xl-diffusers", "text-to-image", "lora", "base_model:stabilityai/stable-diffusion-xl-base-1.0", "base_model:adapter:stabilityai/stable-diffusion-xl-base-1.0", "license:openrail++", "region:us" ]	text-to-image	2023-08-16T06:27:57Z	--- license: openrail++ base_model: stabilityai/stable-diffusion-xl-base-1.0 instance_prompt: a photo of sks woman tags: - stable-diffusion-xl - stable-diffusion-xl-diffusers - text-to-image - diffusers - lora inference: true --- # LoRA DreamBooth - LinoyTsaban/lora-trained-xl-colab-woman-5e-06-1000 These are LoRA adaption weights for stabilityai/stable-diffusion-xl-base-1.0. The weights were trained on a photo of sks woman using [DreamBooth](https://dreambooth.github.io/). You can find some example images in the following. LoRA for the text encoder was enabled: False. Special VAE used for training: madebyollin/sdxl-vae-fp16-fix.
tulayturanmaku/bert2bert_law_summarization	tulayturanmaku	2023-08-16T08:03:17Z	103	0	transformers	[ "transformers", "pytorch", "tensorboard", "encoder-decoder", "text2text-generation", "generated_from_trainer", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text2text-generation	2023-08-16T07:37:48Z	--- tags: - generated_from_trainer metrics: - rouge model-index: - name: bert2bert_law_summarization results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # bert2bert_law_summarization This model is a fine-tuned version of [mrm8488/bert2bert_shared-turkish-summarization](https://huggingface.co/mrm8488/bert2bert_shared-turkish-summarization) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.1184 - Rouge1: 0.6064 - Rouge2: 0.5608 - Rougel: 0.5828 - Rougelsum: 0.5836 - Gen Len: 63.2615 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 4 - mixed_precision_training: Native AMP ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Rouge1 \| Rouge2 \| Rougel \| Rougelsum \| Gen Len \| \|:-------------:\|:-----:\|:----:\|:---------------:\|:------:\|:------:\|:------:\|:---------:\|:-------:\| \| 1.5546 \| 1.0 \| 520 \| 1.2699 \| 0.6047 \| 0.5588 \| 0.5795 \| 0.5799 \| 62.7038 \| \| 1.071 \| 2.0 \| 1040 \| 1.1607 \| 0.6075 \| 0.5598 \| 0.5814 \| 0.5824 \| 63.2269 \| \| 0.9101 \| 3.0 \| 1560 \| 1.1268 \| 0.6129 \| 0.569 \| 0.5884 \| 0.5891 \| 62.9654 \| \| 0.798 \| 4.0 \| 2080 \| 1.1184 \| 0.6064 \| 0.5608 \| 0.5828 \| 0.5836 \| 63.2615 \| ### Framework versions - Transformers 4.28.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3

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