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AptaArkana
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indonesian_bert_case_model_nergrit

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  1. README.md +14 -14
  2. config.json +1 -1
  3. model.safetensors +1 -1
  4. runs/Feb29_07-29-18_6beae0564082/events.out.tfevents.1709191760.6beae0564082.167.0 +3 -0
  5. training_args.bin +2 -2
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [Davlan/bert-base-multilingual-cased-ner-hrl](https://huggingface.co/Davlan/bert-base-multilingual-cased-ner-hrl) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3367
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- - Precision: 0.8139
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- - Recall: 0.8422
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- - F1: 0.8278
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- - Accuracy: 0.9420
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  ## Model description
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@@ -55,19 +55,19 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 0.2503 | 1.0 | 1567 | 0.2331 | 0.7484 | 0.8148 | 0.7802 | 0.9294 |
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- | 0.1645 | 2.0 | 3134 | 0.2307 | 0.7987 | 0.8158 | 0.8072 | 0.9363 |
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- | 0.1097 | 3.0 | 4701 | 0.2588 | 0.7764 | 0.8334 | 0.8039 | 0.9360 |
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- | 0.0822 | 4.0 | 6268 | 0.2624 | 0.8056 | 0.8389 | 0.8219 | 0.9409 |
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- | 0.061 | 5.0 | 7835 | 0.2927 | 0.8183 | 0.8275 | 0.8229 | 0.9414 |
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- | 0.0407 | 6.0 | 9402 | 0.3156 | 0.8021 | 0.8350 | 0.8182 | 0.9399 |
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- | 0.0315 | 7.0 | 10969 | 0.3257 | 0.8102 | 0.8381 | 0.8239 | 0.9413 |
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- | 0.0238 | 8.0 | 12536 | 0.3367 | 0.8139 | 0.8422 | 0.8278 | 0.9420 |
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  ### Framework versions
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- - Transformers 4.35.2
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  - Pytorch 2.1.0+cu121
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  - Datasets 2.17.1
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  - Tokenizers 0.15.2
 
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  This model is a fine-tuned version of [Davlan/bert-base-multilingual-cased-ner-hrl](https://huggingface.co/Davlan/bert-base-multilingual-cased-ner-hrl) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.3309
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+ - Precision: 0.8120
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+ - Recall: 0.8430
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+ - F1: 0.8272
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+ - Accuracy: 0.9423
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.2528 | 1.0 | 1567 | 0.2352 | 0.7442 | 0.8116 | 0.7765 | 0.9282 |
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+ | 0.1653 | 2.0 | 3134 | 0.2250 | 0.8008 | 0.8218 | 0.8112 | 0.9378 |
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+ | 0.1125 | 3.0 | 4701 | 0.2545 | 0.7703 | 0.8381 | 0.8028 | 0.9343 |
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+ | 0.083 | 4.0 | 6268 | 0.2633 | 0.8065 | 0.8353 | 0.8206 | 0.9401 |
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+ | 0.0602 | 5.0 | 7835 | 0.2860 | 0.8124 | 0.8229 | 0.8176 | 0.9413 |
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+ | 0.0411 | 6.0 | 9402 | 0.3129 | 0.8026 | 0.8353 | 0.8186 | 0.9404 |
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+ | 0.0324 | 7.0 | 10969 | 0.3180 | 0.8036 | 0.8400 | 0.8214 | 0.9418 |
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+ | 0.0248 | 8.0 | 12536 | 0.3309 | 0.8120 | 0.8430 | 0.8272 | 0.9423 |
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  ### Framework versions
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+ - Transformers 4.37.2
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  - Pytorch 2.1.0+cu121
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  - Datasets 2.17.1
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  - Tokenizers 0.15.2
config.json CHANGED
@@ -107,7 +107,7 @@
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  "pooler_type": "first_token_transform",
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  "position_embedding_type": "absolute",
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  "torch_dtype": "float32",
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- "transformers_version": "4.35.2",
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  "type_vocab_size": 2,
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  "use_cache": true,
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  "vocab_size": 119547
 
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  "pooler_type": "first_token_transform",
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  "position_embedding_type": "absolute",
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  "torch_dtype": "float32",
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+ "transformers_version": "4.37.2",
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  "type_vocab_size": 2,
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  "use_cache": true,
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  "vocab_size": 119547
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