distilbert_km_5_v2
This model is a fine-tuned version of on the Hartunka/processed_wikitext-103-raw-v1-km-5_v2 dataset. It achieves the following results on the evaluation set:
- Loss: 6.0633
- Accuracy: 0.1558
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: 0.0001
- train_batch_size: 96
- eval_batch_size: 96
- seed: 10
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- num_epochs: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 6.3534 | 4.1982 | 10000 | 6.3199 | 0.1510 |
| 6.0866 | 8.3963 | 20000 | 6.2498 | 0.1533 |
| 5.9471 | 12.5945 | 30000 | 6.2056 | 0.1551 |
| 5.862 | 16.7926 | 40000 | 6.2150 | 0.1530 |
| 5.8189 | 20.9908 | 50000 | 6.1598 | 0.1531 |
Framework versions
- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1
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Evaluation results
- Accuracy on Hartunka/processed_wikitext-103-raw-v1-km-5_v2self-reported0.156