distilbert-llm-aug
This model is a fine-tuned version of distilbert/distilbert-base-multilingual-cased on the marcgrec/ag_news-llm-aug dataset. It achieves the following results on the evaluation set:
- Loss: 0.8359
- F1: 0.8662
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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| No log | 1.0 | 125 | 0.4586 | 0.8584 |
| No log | 2.0 | 250 | 0.6775 | 0.8358 |
| No log | 3.0 | 375 | 0.6700 | 0.8606 |
| 0.194 | 4.0 | 500 | 0.7256 | 0.8663 |
| 0.194 | 5.0 | 625 | 0.7641 | 0.8673 |
| 0.194 | 6.0 | 750 | 0.8083 | 0.8645 |
| 0.194 | 7.0 | 875 | 0.8237 | 0.8655 |
| 0.0016 | 8.0 | 1000 | 0.8078 | 0.8660 |
| 0.0016 | 9.0 | 1125 | 0.8227 | 0.8654 |
| 0.0016 | 10.0 | 1250 | 0.8359 | 0.8662 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.9.0+cu128
- Datasets 4.3.0
- Tokenizers 0.22.1
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