mistral-0.5B-base
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.8893
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: 0.0005
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 5.9695 | 0.3989 | 74 | 6.0154 |
| 5.0148 | 0.7978 | 148 | 5.1781 |
| 4.459 | 1.1941 | 222 | 4.7603 |
| 4.0585 | 1.5930 | 296 | 4.4421 |
| 3.8404 | 1.9919 | 370 | 4.2375 |
| 3.1164 | 2.3881 | 444 | 4.0944 |
| 2.4948 | 2.7871 | 518 | 3.9528 |
| 1.6126 | 3.1833 | 592 | 3.9094 |
| 1.5873 | 3.5822 | 666 | 3.8964 |
| 1.4401 | 3.9811 | 740 | 3.8893 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0