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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-1.5B-Instruct |
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tags: |
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- base_model:adapter:Qwen/Qwen2.5-Coder-1.5B-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: qwen2.5_1.5b_coder_dslearn_os_sft |
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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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# qwen2.5_1.5b_coder_dslearn_os_sft |
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This model is a fine-tuned version of [Qwen/Qwen2.5-Coder-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-1.5B-Instruct) on an unknown dataset. |
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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: 0.0002 |
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- train_batch_size: 1 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 32 |
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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: cosine |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 3 |
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### Training results |
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### Framework versions |
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- PEFT 0.16.0 |
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- Transformers 4.53.2 |
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- Pytorch 2.5.1 |
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- Datasets 4.0.0 |
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- Tokenizers 0.21.2 |
