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--- |
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license: mit |
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tags: |
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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: biogpt-new |
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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: validation |
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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: 0.4968085106382979 |
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- name: Recall |
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type: recall |
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value: 0.5933926302414231 |
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- name: F1 |
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type: f1 |
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value: 0.540822235089751 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9570189427826831 |
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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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should probably proofread and complete it, then remove this comment. --> |
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# biogpt-new |
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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: 0.1984 |
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- Precision: 0.4968 |
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- Recall: 0.5934 |
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- F1: 0.5408 |
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- Accuracy: 0.9570 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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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: 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: 5 |
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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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| 0.1683 | 1.0 | 680 | 0.1669 | 0.3778 | 0.4752 | 0.4209 | 0.9512 | |
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| 0.1407 | 2.0 | 1360 | 0.1529 | 0.4183 | 0.5337 | 0.4690 | 0.9521 | |
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| 0.0813 | 3.0 | 2040 | 0.1548 | 0.4751 | 0.5820 | 0.5231 | 0.9570 | |
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| 0.0592 | 4.0 | 2720 | 0.1762 | 0.4966 | 0.5565 | 0.5249 | 0.9582 | |
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| 0.051 | 5.0 | 3400 | 0.1984 | 0.4968 | 0.5934 | 0.5408 | 0.9570 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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