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---
license: cc0-1.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: CancerTextV2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# CancerTextV2
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.
It achieves the following results on the evaluation set:
- Loss: 0.5913
- Accuracy: 0.8692
- Precision: 0.8666
- Recall: 0.8738
- F1: 0.8701
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.4717 | 1.0 | 600 | 0.3318 | 0.8617 | 0.8562 | 0.8704 | 0.8633 |
| 0.3248 | 2.0 | 1200 | 0.3144 | 0.8658 | 0.8821 | 0.8455 | 0.8634 |
| 0.2653 | 3.0 | 1800 | 0.3519 | 0.8625 | 0.8507 | 0.8804 | 0.8653 |
| 0.2164 | 4.0 | 2400 | 0.4090 | 0.8658 | 0.9002 | 0.8239 | 0.8604 |
| 0.1884 | 5.0 | 3000 | 0.4413 | 0.8667 | 0.8850 | 0.8439 | 0.8639 |
| 0.1582 | 6.0 | 3600 | 0.4415 | 0.865 | 0.8971 | 0.8256 | 0.8599 |
| 0.1377 | 7.0 | 4200 | 0.5165 | 0.8708 | 0.8694 | 0.8738 | 0.8716 |
| 0.1192 | 8.0 | 4800 | 0.5699 | 0.8675 | 0.8826 | 0.8488 | 0.8654 |
| 0.1081 | 9.0 | 5400 | 0.5837 | 0.8692 | 0.8666 | 0.8738 | 0.8701 |
| 0.1018 | 10.0 | 6000 | 0.5913 | 0.8692 | 0.8666 | 0.8738 | 0.8701 |
### Framework versions
- Transformers 4.21.2
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
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