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--- |
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license: apache-2.0 |
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tags: |
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- summarisation |
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- generated_from_trainer |
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metrics: |
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- rouge |
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model-index: |
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- name: bert-small2bert-small-finetuned-cnn_daily_mail-summarization-finetuned-bbc-news-extracted-sumy |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# bert-small2bert-small-finetuned-cnn_daily_mail-summarization-finetuned-bbc-news-extracted-sumy |
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This model is a fine-tuned version of [mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization](https://huggingface.co/mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3228 |
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- Rouge1: 56.5706 |
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- Rouge2: 43.0906 |
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- Rougel: 47.9957 |
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- Rougelsum: 53.417 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5.6e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
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| 0.3226 | 1.0 | 223 | 0.3225 | 55.7639 | 41.9414 | 46.9804 | 52.5639 | |
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| 0.262 | 2.0 | 446 | 0.3198 | 55.7522 | 42.0929 | 46.8388 | 52.6659 | |
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| 0.2153 | 3.0 | 669 | 0.3195 | 55.7091 | 42.2111 | 47.2641 | 52.5765 | |
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| 0.1805 | 4.0 | 892 | 0.3164 | 55.8115 | 42.5536 | 47.3529 | 52.7672 | |
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| 0.1527 | 5.0 | 1115 | 0.3203 | 56.8658 | 43.4238 | 48.2268 | 53.8136 | |
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| 0.14 | 6.0 | 1338 | 0.3234 | 55.7138 | 41.8562 | 46.8362 | 52.5201 | |
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| 0.1252 | 7.0 | 1561 | 0.3228 | 56.5706 | 43.0906 | 47.9957 | 53.417 | |
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| 0.1229 | 8.0 | 1784 | 0.3228 | 56.5706 | 43.0906 | 47.9957 | 53.417 | |
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### Framework versions |
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- Transformers 4.21.0 |
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- Pytorch 1.12.0+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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