lenate_model_11_distilbert_trained
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5964
- Accuracy: 0.7332
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: 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 |
|---|---|---|---|---|
| No log | 1.0 | 355 | 0.6187 | 0.7163 |
| 0.668 | 2.0 | 710 | 0.5964 | 0.7332 |
| 0.4256 | 3.0 | 1065 | 0.6048 | 0.7615 |
| 0.4256 | 4.0 | 1420 | 0.6930 | 0.7685 |
| 0.2576 | 5.0 | 1775 | 0.8426 | 0.7502 |
| 0.1593 | 6.0 | 2130 | 1.0264 | 0.7565 |
| 0.1593 | 7.0 | 2485 | 1.1487 | 0.7586 |
| 0.0968 | 8.0 | 2840 | 1.3436 | 0.7530 |
| 0.0456 | 9.0 | 3195 | 1.3743 | 0.7594 |
| 0.0342 | 10.0 | 3550 | 1.3954 | 0.7594 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2