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bioBERT-finetuned-FPB-and-FiQA

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End of training

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  1. README.md +7 -9
  2. model.safetensors +1 -1
  3. runs/Nov08_23-10-59_a61085e89b5d/events.out.tfevents.1699485060.a61085e89b5d.2309.16 +2 -2
  4. runs/Nov08_23-10-59_a61085e89b5d/events.out.tfevents.1699485358.a61085e89b5d.2309.17 +3 -0
README.md CHANGED
@@ -16,8 +16,8 @@ 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-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5722
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- - F1: 0.7947
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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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- - num_epochs: 5
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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- | No log | 1.0 | 329 | 0.5722 | 0.7947 |
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- | 0.2248 | 2.0 | 658 | 0.6955 | 0.7764 |
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- | 0.2248 | 3.0 | 987 | 0.7126 | 0.7784 |
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- | 0.1902 | 4.0 | 1316 | 0.7492 | 0.7733 |
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- | 0.1636 | 5.0 | 1645 | 0.7840 | 0.7631 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4646
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+ - F1: 0.7724
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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: 5e-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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+ - num_epochs: 3
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | No log | 1.0 | 329 | 0.4844 | 0.7703 |
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+ | 0.4986 | 2.0 | 658 | 0.4646 | 0.7724 |
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+ | 0.4986 | 3.0 | 987 | 0.6034 | 0.7572 |
 
 
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  ### Framework versions
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