deepseek-r1-1.5b-finetuned
This model is a fine-tuned version of deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2611
- Accuracy: 0.8721
- Precision: 0.8752
- Recall: 0.8721
- F1: 0.8726
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: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 3.3097 | 1.0 | 49 | 0.3026 | 0.8372 | 0.8390 | 0.8372 | 0.8377 |
| 0.8218 | 2.0 | 98 | 0.2645 | 0.8721 | 0.8752 | 0.8721 | 0.8726 |
| 0.9199 | 3.0 | 147 | 0.2611 | 0.8721 | 0.8752 | 0.8721 | 0.8726 |
Framework versions
- Transformers 5.12.1
- Pytorch 2.11.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2