Millesime-202608-4B-phase1
This model is a fine-tuned version of Qwen/Qwen3-4B-Instruct-2507 on the millesime_202608_sft dataset. It achieves the following results on the evaluation set:
- Loss: 0.9014
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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- total_eval_batch_size: 16
- 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: cosine
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 2.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.0220 | 0.4228 | 500 | 0.9928 |
| 0.9338 | 0.8457 | 1000 | 0.9309 |
| 0.6958 | 1.2681 | 1500 | 0.9176 |
| 0.6838 | 1.6909 | 2000 | 0.9042 |
| 0.6903 | 2.0 | 2366 | 0.9014 |
Framework versions
- Transformers 5.8.0
- Pytorch 2.13.0+cu130
- Datasets 4.0.0
- Tokenizers 0.22.2