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--- |
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license: cc0-1.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: CancerTextV2 |
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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 |
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should probably proofread and complete it, then remove this comment. --> |
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# CancerTextV2 |
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This model is a fine-tuned version of [bionlp/bluebert_pubmed_uncased_L-12_H-768_A-12](https://huggingface.co/bionlp/bluebert_pubmed_uncased_L-12_H-768_A-12) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5913 |
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- Accuracy: 0.8692 |
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- Precision: 0.8666 |
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- Recall: 0.8738 |
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- F1: 0.8701 |
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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: 1e-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: 10 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.4717 | 1.0 | 600 | 0.3318 | 0.8617 | 0.8562 | 0.8704 | 0.8633 | |
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| 0.3248 | 2.0 | 1200 | 0.3144 | 0.8658 | 0.8821 | 0.8455 | 0.8634 | |
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| 0.2653 | 3.0 | 1800 | 0.3519 | 0.8625 | 0.8507 | 0.8804 | 0.8653 | |
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| 0.2164 | 4.0 | 2400 | 0.4090 | 0.8658 | 0.9002 | 0.8239 | 0.8604 | |
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| 0.1884 | 5.0 | 3000 | 0.4413 | 0.8667 | 0.8850 | 0.8439 | 0.8639 | |
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| 0.1582 | 6.0 | 3600 | 0.4415 | 0.865 | 0.8971 | 0.8256 | 0.8599 | |
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| 0.1377 | 7.0 | 4200 | 0.5165 | 0.8708 | 0.8694 | 0.8738 | 0.8716 | |
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| 0.1192 | 8.0 | 4800 | 0.5699 | 0.8675 | 0.8826 | 0.8488 | 0.8654 | |
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| 0.1081 | 9.0 | 5400 | 0.5837 | 0.8692 | 0.8666 | 0.8738 | 0.8701 | |
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| 0.1018 | 10.0 | 6000 | 0.5913 | 0.8692 | 0.8666 | 0.8738 | 0.8701 | |
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### Framework versions |
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- Transformers 4.21.2 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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