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--- |
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library_name: peft |
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license: mit |
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base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: deepseek_finetuned |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# deepseek_finetuned |
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This model is a fine-tuned version of [deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B](https://huggingface.co/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3560 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 64 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 3 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 3.926 | 0.1429 | 100 | 1.3948 | |
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| 0.6639 | 0.2857 | 200 | 0.4467 | |
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| 0.4304 | 0.4286 | 300 | 0.4228 | |
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| 0.4158 | 0.5714 | 400 | 0.4118 | |
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| 0.4046 | 0.7143 | 500 | 0.4031 | |
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| 0.3968 | 0.8571 | 600 | 0.3952 | |
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| 0.3925 | 1.0 | 700 | 0.3888 | |
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| 0.3864 | 1.1429 | 800 | 0.3834 | |
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| 0.3781 | 1.2857 | 900 | 0.3785 | |
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| 0.3759 | 1.4286 | 1000 | 0.3743 | |
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| 0.3696 | 1.5714 | 1100 | 0.3708 | |
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| 0.3679 | 1.7143 | 1200 | 0.3675 | |
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| 0.3664 | 1.8571 | 1300 | 0.3647 | |
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| 0.3637 | 2.0 | 1400 | 0.3626 | |
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| 0.3607 | 2.1429 | 1500 | 0.3607 | |
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| 0.3573 | 2.2857 | 1600 | 0.3592 | |
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| 0.3607 | 2.4286 | 1700 | 0.3580 | |
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| 0.3561 | 2.5714 | 1800 | 0.3571 | |
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| 0.357 | 2.7143 | 1900 | 0.3564 | |
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| 0.354 | 2.8571 | 2000 | 0.3561 | |
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| 0.3548 | 3.0 | 2100 | 0.3560 | |
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### Framework versions |
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- PEFT 0.14.0 |
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- Transformers 4.48.2 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
