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--- |
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librar_yname: transformers |
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license: other |
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base_model: Qwen/Qwen2.5-1.5B-Instruct |
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tags: |
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- llama-factory |
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- freeze |
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- generated_from_trainer |
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model-index: |
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- name: output |
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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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# output |
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This model is a fine-tuned version of Qwen2.5-1.5B-Instruct on the alpaca_zh_demo dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9959 |
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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: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 2 |
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- optimizer: Use 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_ratio: 0.1 |
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- num_epochs: 3.0 |
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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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| 1.0102 | 1.1111 | 500 | 1.7723 | |
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| 0.5375 | 2.2222 | 1000 | 1.9768 | |
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### Framework versions |
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- Transformers 4.46.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 3.0.2 |
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- Tokenizers 0.20.3 |
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