full_sft_sc7b
This model is a fine-tuned version of deepseek-ai/DeepSeek-R1-Distill-Qwen-7B on the sc_7b dataset. It achieves the following results on the evaluation set:
- Loss: 0.3349
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: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 8
- total_eval_batch_size: 4
- 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
- num_epochs: 2.0
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.2319 | 0.4798 | 500 | 0.3270 |
| 0.3837 | 0.9597 | 1000 | 0.3208 |
| 0.1362 | 1.4395 | 1500 | 0.3367 |
| 0.1385 | 1.9194 | 2000 | 0.3348 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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Base model
deepseek-ai/DeepSeek-R1-Distill-Qwen-7B