lr1e5-layer1-bs16-Distil-CNN256LSTM128NoBi
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: 1.3317
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.4525 | 1.0 | 3290 | 1.2824 |
| 1.045 | 2.0 | 6580 | 1.1619 |
| 0.7652 | 3.0 | 9870 | 1.1751 |
| 0.5353 | 4.0 | 13160 | 1.3317 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3