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---
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license: apache-2.0
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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: CancerTextV1
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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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# CancerTextV1
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5476
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- Accuracy: 0.8683
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- Precision: 0.8558
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- Recall: 0.8870
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- F1: 0.8711
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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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| 0.3268 | 1.0 | 600 | 0.3939 | 0.8475 | 0.8268 | 0.8804 | 0.8528 |
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| 0.3132 | 2.0 | 1200 | 0.3510 | 0.8475 | 0.8509 | 0.8439 | 0.8474 |
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| 0.2595 | 3.0 | 1800 | 0.3631 | 0.8617 | 0.8505 | 0.8787 | 0.8644 |
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| 0.2256 | 4.0 | 2400 | 0.4303 | 0.8625 | 0.8507 | 0.8804 | 0.8653 |
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| 0.1944 | 5.0 | 3000 | 0.4551 | 0.8642 | 0.8592 | 0.8721 | 0.8656 |
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| 0.1734 | 6.0 | 3600 | 0.4673 | 0.86 | 0.8434 | 0.8854 | 0.8639 |
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| 0.1446 | 7.0 | 4200 | 0.4960 | 0.87 | 0.8562 | 0.8904 | 0.8730 |
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| 0.1371 | 8.0 | 4800 | 0.5162 | 0.8708 | 0.8646 | 0.8804 | 0.8724 |
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| 0.123 | 9.0 | 5400 | 0.5396 | 0.8642 | 0.8604 | 0.8704 | 0.8654 |
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| 0.1174 | 10.0 | 6000 | 0.5476 | 0.8683 | 0.8558 | 0.8870 | 0.8711 |
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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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