Model: formalmathatepfl/qwen3-8b-sft Source: Original Platform
library_name, license, base_model, tags, model-index
| library_name | license | base_model | tags | model-index | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| transformers | other | Qwen/Qwen3-8B |
|
|
Qwen3-no-feedback
This model is a fine-tuned version of Qwen/Qwen3-8B on the sft dataset. It achieves the following results on the evaluation set:
- Loss: 0.0647
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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 7
- total_train_batch_size: 14
- total_eval_batch_size: 14
- 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_ratio: 0.05
- num_epochs: 1.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.0813 | 0.2120 | 1000 | 0.0781 |
| 0.0717 | 0.4240 | 2000 | 0.0712 |
| 0.0664 | 0.6360 | 3000 | 0.0669 |
| 0.0659 | 0.8480 | 4000 | 0.0651 |
Framework versions
- Transformers 4.57.6
- Pytorch 2.9.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
Description
Languages
Jinja
100%