SFT-Qwen3-30B-dsetV3
This model is a fine-tuned version of Qwen/Qwen3-Coder-30B-A3B-Instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6872
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: 0.0002
- train_batch_size: 5
- eval_batch_size: 5
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 10
- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.7767 | 0.625 | 30 | 0.7523 |
| 0.568 | 1.25 | 60 | 0.7073 |
| 0.5549 | 1.875 | 90 | 0.6872 |
| 0.3923 | 2.5 | 120 | 0.6952 |
| 0.4057 | 3.125 | 150 | 0.7339 |
| 0.213 | 3.75 | 180 | 0.7525 |
Framework versions
- PEFT 0.18.0
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.4.1
- Tokenizers 0.22.1
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Model tree for tam2003/SFT-Qwen3-30B-dsetV3
Base model
Qwen/Qwen3-Coder-30B-A3B-Instruct