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update model card README.md

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@@ -4,9 +4,36 @@ tags:
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  - generated_from_trainer
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  datasets:
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  - ncbi_disease
 
 
 
 
 
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  model-index:
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  - name: finetuned-biogpt
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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
@@ -15,6 +42,12 @@ should probably proofread and complete it, then remove this comment. -->
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  # finetuned-biogpt
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  This model is a fine-tuned version of [microsoft/biogpt](https://huggingface.co/microsoft/biogpt) on the ncbi_disease dataset.
 
 
 
 
 
 
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  ## Model description
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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: 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: 3
 
 
 
 
 
 
 
 
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  ### Framework versions
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  - generated_from_trainer
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  datasets:
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  - ncbi_disease
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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: finetuned-biogpt
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+ results:
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+ - task:
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+ name: Token Classification
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+ type: token-classification
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+ dataset:
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+ name: ncbi_disease
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+ type: ncbi_disease
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+ config: ncbi_disease
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+ split: test
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+ args: ncbi_disease
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+ metrics:
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+ - name: Precision
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+ type: precision
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+ value: 0.0761904761904762
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+ - name: Recall
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+ type: recall
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+ value: 0.058333333333333334
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+ - name: F1
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+ type: f1
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+ value: 0.06607669616519174
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9220180016640194
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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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  # finetuned-biogpt
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  This model is a fine-tuned version of [microsoft/biogpt](https://huggingface.co/microsoft/biogpt) on the ncbi_disease dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2503
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+ - Precision: 0.0762
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+ - Recall: 0.0583
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+ - F1: 0.0661
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+ - Accuracy: 0.9220
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  ## Model description
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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: 2
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 340 | 0.2644 | 0.0426 | 0.0281 | 0.0339 | 0.9183 |
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+ | 0.3055 | 2.0 | 680 | 0.2503 | 0.0762 | 0.0583 | 0.0661 | 0.9220 |
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+
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  ### Framework versions
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