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--- |
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library_name: peft |
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license: apache-2.0 |
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base_model: Qwen/Qwen2.5-Coder-7B-Instruct |
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tags: |
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- base_model:adapter:Qwen/Qwen2.5-Coder-7B-Instruct |
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- lora |
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- transformers |
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pipeline_tag: text-generation |
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model-index: |
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- name: SFT-Qwen2.5-Coder-7B_v1.2s |
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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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# SFT-Qwen2.5-Coder-7B_v1.2s |
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This model is a fine-tuned version of [Qwen/Qwen2.5-Coder-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5014 |
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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: 0.0001 |
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- train_batch_size: 2 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT 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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- lr_scheduler_warmup_ratio: 0.03 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.8618 | 0.1985 | 20 | 0.7028 | |
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| 0.6786 | 0.3970 | 40 | 0.6255 | |
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| 0.5624 | 0.5955 | 60 | 0.5838 | |
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| 0.5455 | 0.7940 | 80 | 0.5579 | |
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| 0.531 | 0.9926 | 100 | 0.5395 | |
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| 0.3587 | 1.1886 | 120 | 0.5308 | |
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| 0.4215 | 1.3871 | 140 | 0.5241 | |
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| 0.4159 | 1.5856 | 160 | 0.5155 | |
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| 0.4262 | 1.7841 | 180 | 0.5045 | |
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| 0.4629 | 1.9826 | 200 | 0.5014 | |
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| 0.344 | 2.1787 | 220 | 0.5186 | |
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| 0.3075 | 2.3772 | 240 | 0.5144 | |
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| 0.3312 | 2.5757 | 260 | 0.5061 | |
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### Framework versions |
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- PEFT 0.18.0 |
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- Transformers 4.57.3 |
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- Pytorch 2.9.0+cu126 |
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- Datasets 4.4.1 |
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- Tokenizers 0.22.1 |
