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cer

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  1. README.md +10 -12
  2. model.safetensors +1 -1
  3. runs/Feb18_15-57-13_25a8e1be9559/events.out.tfevents.1708271834.25a8e1be9559.26.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [dmis-lab/biobert-base-cased-v1.1](https://huggingface.co/dmis-lab/biobert-base-cased-v1.1) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4254
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- - Precision: 0.9224
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- - Recall: 0.8589
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- - F1: 0.8895
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- - Accuracy: 0.9318
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 2e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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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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  - lr_scheduler_warmup_ratio: 0.2
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- - num_epochs: 3
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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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- | 0.0212 | 1.0 | 4841 | 0.3474 | 0.9107 | 0.8663 | 0.8879 | 0.9305 |
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- | 0.0029 | 2.0 | 9682 | 0.3771 | 0.9206 | 0.8603 | 0.8894 | 0.9322 |
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- | 0.0008 | 3.0 | 14523 | 0.4254 | 0.9224 | 0.8589 | 0.8895 | 0.9318 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [dmis-lab/biobert-base-cased-v1.1](https://huggingface.co/dmis-lab/biobert-base-cased-v1.1) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5760
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+ - Precision: 0.6022
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+ - Recall: 0.6740
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+ - F1: 0.6361
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+ - Accuracy: 0.7627
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 2e-07
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  - train_batch_size: 16
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  - eval_batch_size: 16
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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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  - lr_scheduler_warmup_ratio: 0.2
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+ - num_epochs: 1
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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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+ | 0.5369 | 1.0 | 4841 | 0.5760 | 0.6022 | 0.6740 | 0.6361 | 0.7627 |
 
 
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  ### Framework versions
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