Qwen3-4B_Paper_Impact_SFT_1ep
This model is a fine-tuned version of Qwen/Qwen3-4B-Instruct-2507 on the paper_impact_sft_train dataset. It achieves the following results on the evaluation set:
- Loss: 0.0648
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 32
- 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_ratio: 0.1
- num_epochs: 1.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.0499 | 0.3614 | 500 | 0.0628 |
| 0.0333 | 0.7228 | 1000 | 0.0623 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.22.1
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Model tree for FlyPig23/Qwen3-4B_Paper_Impact_SFT_1ep
Base model
Qwen/Qwen3-4B-Instruct-2507