google-bert-base-uncased-f1_937
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README.md
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base_model: google-bert/bert-base-uncased
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tags:
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- generated_from_trainer
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model-index:
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- name: nlpcw_bert-base-uncased-abbr
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results: []
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# nlpcw_bert-base-uncased-abbr
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This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
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## Model description
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- lr_scheduler_type: linear
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- num_epochs: 10
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### Framework versions
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- Transformers 4.40.0
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base_model: google-bert/bert-base-uncased
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: nlpcw_bert-base-uncased-abbr
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results: []
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# nlpcw_bert-base-uncased-abbr
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This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2675
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- Precision: 0.9390
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- Recall: 0.9349
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- F1: 0.9369
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- Accuracy: 0.9317
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## Model description
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- lr_scheduler_type: linear
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.6325 | 1.0 | 67 | 0.2629 | 0.9036 | 0.9090 | 0.9063 | 0.9043 |
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| 0.3169 | 2.0 | 134 | 0.2297 | 0.9309 | 0.9137 | 0.9223 | 0.9182 |
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| 0.1994 | 3.0 | 201 | 0.2282 | 0.9310 | 0.9193 | 0.9251 | 0.9223 |
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| 0.17 | 4.0 | 268 | 0.2193 | 0.9366 | 0.9286 | 0.9326 | 0.9278 |
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| 0.1457 | 5.0 | 335 | 0.2350 | 0.9395 | 0.9373 | 0.9384 | 0.9331 |
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| 0.1086 | 6.0 | 402 | 0.2435 | 0.9418 | 0.9340 | 0.9379 | 0.9331 |
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| 0.0908 | 7.0 | 469 | 0.2537 | 0.9357 | 0.9283 | 0.9319 | 0.9270 |
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| 0.0791 | 8.0 | 536 | 0.2675 | 0.9390 | 0.9349 | 0.9369 | 0.9317 |
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### Framework versions
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- Transformers 4.40.0
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