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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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