Mistral-8B-Instruct-2410-2025-II
This model is a fine-tuned version of mistralai/Ministral-8B-Instruct-2410 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5701
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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.3018 | 0.8658 | 100 | 1.3113 |
| 1.1356 | 1.7273 | 200 | 1.1116 |
| 0.9729 | 2.5887 | 300 | 0.9593 |
| 0.7977 | 3.4502 | 400 | 0.8432 |
| 0.7237 | 4.3117 | 500 | 0.7587 |
| 0.6048 | 5.1732 | 600 | 0.6926 |
| 0.6142 | 6.0346 | 700 | 0.6468 |
| 0.5462 | 6.9004 | 800 | 0.6196 |
| 0.5386 | 7.7619 | 900 | 0.5937 |
| 0.5375 | 8.6234 | 1000 | 0.5801 |
| 0.4623 | 9.4848 | 1100 | 0.5701 |
Framework versions
- PEFT 0.8.2
- Transformers 4.57.1
- Pytorch 2.7.1+cu118
- Datasets 4.2.0
- Tokenizers 0.22.1
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mistralai/Ministral-8B-Instruct-2410