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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: 2023MLMA_LAB9_task2 |
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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: 0.4622186495176849 |
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- name: Recall |
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type: recall |
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value: 0.555019305019305 |
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- name: F1 |
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type: f1 |
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value: 0.5043859649122807 |
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- name: Accuracy |
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type: accuracy |
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value: 0.9518067602785016 |
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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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# 2023MLMA_LAB9_task2 |
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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: 0.1673 |
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- Precision: 0.4622 |
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- Recall: 0.5550 |
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- F1: 0.5044 |
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- Accuracy: 0.9518 |
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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: 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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| 0.306 | 1.0 | 679 | 0.1701 | 0.3764 | 0.3938 | 0.3849 | 0.9442 | |
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| 0.1752 | 2.0 | 1358 | 0.1638 | 0.4538 | 0.5261 | 0.4873 | 0.9509 | |
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| 0.1072 | 3.0 | 2037 | 0.1673 | 0.4622 | 0.5550 | 0.5044 | 0.9518 | |
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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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