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distilbert-base-uncased-OMDENA-cllbck
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: 0.0158
- Accuracy: 0.9988
- Precision: 0.9988
- Recall: 0.9983
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: 0.0002
- 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
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall |
---|---|---|---|---|---|---|
0.3301 | 1.0 | 409 | 0.0433 | 0.9890 | 0.9891 | 0.9888 |
0.0517 | 2.0 | 818 | 0.0538 | 0.9914 | 0.9916 | 0.9914 |
0.0373 | 3.0 | 1227 | 0.0193 | 0.9976 | 0.9974 | 0.9972 |
0.0163 | 4.0 | 1636 | 0.0180 | 0.9963 | 0.9967 | 0.9962 |
0.0304 | 5.0 | 2045 | 0.0176 | 0.9976 | 0.9978 | 0.9971 |
0.0103 | 6.0 | 2454 | 0.0158 | 0.9988 | 0.9988 | 0.9983 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3