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distilbert-base-uncased-finetuned-provenances-finetuned-provenances
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.1472
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: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.4101 | 1.0 | 94 | 2.2010 |
| 2.2495 | 2.0 | 188 | 2.0898 |
| 2.1192 | 3.0 | 282 | 2.0020 |
| 2.0862 | 4.0 | 376 | 1.9896 |
| 2.0405 | 5.0 | 470 | 1.9949 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Tokenizers 0.13.3
