code_finetune
This model is a fine-tuned version of deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B on the open_thoughts_19K dataset. It achieves the following results on the evaluation set:
- Loss: 0.5804
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
- total_train_batch_size: 2
- total_eval_batch_size: 2
- 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 |
|---|---|---|---|
| No log | 0.0870 | 2 | 0.6561 |
| No log | 0.1739 | 4 | 0.6379 |
| No log | 0.2609 | 6 | 0.6213 |
| No log | 0.3478 | 8 | 0.6110 |
| No log | 0.4348 | 10 | 0.5980 |
| No log | 0.5217 | 12 | 0.5886 |
| No log | 0.6087 | 14 | 0.5854 |
| No log | 0.6957 | 16 | 0.5828 |
| No log | 0.7826 | 18 | 0.5815 |
| No log | 0.8696 | 20 | 0.5806 |
| No log | 0.9565 | 22 | 0.5804 |
Framework versions
- Transformers 4.50.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
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Base model
deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B