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distilbert-base-uncased-finetuned-dataset
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0135
- Accuracy: 0.9981
- F1: 0.9981
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.2492 | 1.0 | 536 | 0.0170 | 0.9972 | 0.9972 |
| 0.0106 | 2.0 | 1072 | 0.0135 | 0.9981 | 0.9981 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
