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distilbert-base-uncased_finetuned_text_2_disease_cel_v1
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0574
- Accuracy: 0.9985
- F1: 0.9985
- Recall: 0.9985
- Precision: 0.9986
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision |
|---|---|---|---|---|---|---|---|
| 0.8645 | 1.0 | 167 | 0.6333 | 0.9354 | 0.9288 | 0.9354 | 0.9501 |
| 0.1886 | 2.0 | 334 | 0.1070 | 0.9970 | 0.9970 | 0.9970 | 0.9971 |
| 0.0902 | 3.0 | 501 | 0.0574 | 0.9985 | 0.9985 | 0.9985 | 0.9986 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
