disitlbert_finetunedmodel
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: 1.4268
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 |
|---|---|---|---|
| 1.5666 | 1.0 | 520 | 1.2041 |
| 1.2334 | 2.0 | 1040 | 1.1728 |
| 1.1474 | 3.0 | 1560 | 1.1650 |
| 1.0639 | 4.0 | 2080 | 1.2005 |
| 1.0005 | 5.0 | 2600 | 1.1893 |
| 0.9307 | 6.0 | 3120 | 1.2277 |
| 0.872 | 7.0 | 3640 | 1.3071 |
| 0.8073 | 8.0 | 4160 | 1.2973 |
| 0.7666 | 9.0 | 4680 | 1.3650 |
| 0.7281 | 10.0 | 5200 | 1.4268 |
Framework versions
- Transformers 4.30.0
- Pytorch 2.2.1+cu121
- Datasets 2.13.0
- Tokenizers 0.13.3
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