Qwen3.5-9B-full-eSFT
This model is a fine-tuned version of Qwen/Qwen3.5-9B on the vlguard_Qwen3.5-9B_eSFT dataset. It achieves the following results on the evaluation set:
- Loss: 1.1175
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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 128
- total_train_batch_size: 256
- total_eval_batch_size: 2
- optimizer: Use OptimizerNames.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: 0.03
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.8568 | 3.0 | 24 | 1.1175 |
Framework versions
- Transformers 5.6.0
- Pytorch 2.5.1+cu121
- Datasets 4.0.0
- Tokenizers 0.22.2