da_distilbert
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: 1.6301
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: 15
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 130 | 2.0998 |
| No log | 2.0 | 260 | 1.9483 |
| No log | 3.0 | 390 | 1.8376 |
| 2.1352 | 4.0 | 520 | 1.8386 |
| 2.1352 | 5.0 | 650 | 1.7713 |
| 2.1352 | 6.0 | 780 | 1.7591 |
| 2.1352 | 7.0 | 910 | 1.7380 |
| 1.8059 | 8.0 | 1040 | 1.6942 |
| 1.8059 | 9.0 | 1170 | 1.6574 |
| 1.8059 | 10.0 | 1300 | 1.6882 |
| 1.8059 | 11.0 | 1430 | 1.6419 |
| 1.7023 | 12.0 | 1560 | 1.6442 |
| 1.7023 | 13.0 | 1690 | 1.6709 |
| 1.7023 | 14.0 | 1820 | 1.6300 |
| 1.7023 | 15.0 | 1950 | 1.6165 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.4.0.dev20240502
- Datasets 2.19.0
- Tokenizers 0.19.1
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