ggb2
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2504
- Accuracy: 0.7867
- F1: 0.7902
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.7074 | 1.0 | 329 | 0.9372 | 0.6930 | 0.7034 |
| 0.2637 | 2.0 | 658 | 0.7453 | 0.7716 | 0.7691 |
| 0.1483 | 3.0 | 987 | 0.9178 | 0.7637 | 0.7687 |
| 0.1022 | 4.0 | 1316 | 1.1147 | 0.7665 | 0.7742 |
| 0.0695 | 5.0 | 1645 | 1.0453 | 0.7895 | 0.7941 |
| 0.0518 | 6.0 | 1974 | 0.9508 | 0.8185 | 0.8188 |
| 0.0414 | 7.0 | 2303 | 1.1806 | 0.7784 | 0.7831 |
| 0.0324 | 8.0 | 2632 | 1.1893 | 0.7947 | 0.7950 |
| 0.0272 | 9.0 | 2961 | 1.2167 | 0.7927 | 0.7955 |
| 0.0226 | 10.0 | 3290 | 1.2504 | 0.7867 | 0.7902 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3