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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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- f1 |
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- recall |
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- precision |
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base_model: distilbert-base-uncased |
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model-index: |
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- name: distilbert-base-uncased_finetuned_text_2_disease_cel |
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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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# distilbert-base-uncased_finetuned_text_2_disease_cel |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2732 |
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- Accuracy: 0.9865 |
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- F1: 0.9864 |
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- Recall: 0.9865 |
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- Precision: 0.9879 |
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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: 32 |
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- eval_batch_size: 32 |
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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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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:| |
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| 1.3868 | 1.0 | 167 | 1.1692 | 0.8649 | 0.8458 | 0.8649 | 0.8573 | |
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| 0.5345 | 2.0 | 334 | 0.4214 | 0.9745 | 0.9736 | 0.9745 | 0.9769 | |
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| 0.3472 | 3.0 | 501 | 0.2732 | 0.9865 | 0.9864 | 0.9865 | 0.9879 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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