my_awesome_model_priority_3
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: 0.1090
- Accuracy: 0.9875
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: 11
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 10 | 0.8290 | 0.625 |
| No log | 2.0 | 20 | 0.6544 | 0.8187 |
| No log | 3.0 | 30 | 0.4782 | 0.8688 |
| No log | 4.0 | 40 | 0.3593 | 0.9062 |
| No log | 5.0 | 50 | 0.2612 | 0.9313 |
| No log | 6.0 | 60 | 0.2043 | 0.9313 |
| No log | 7.0 | 70 | 0.1709 | 0.9375 |
| No log | 8.0 | 80 | 0.1448 | 0.95 |
| No log | 9.0 | 90 | 0.1236 | 0.9688 |
| No log | 10.0 | 100 | 0.1129 | 0.9875 |
| No log | 11.0 | 110 | 0.1090 | 0.9875 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2