output
This model is a fine-tuned version of Qwen2.5-1.5B-Instruct on the alpaca_zh_demo dataset. It achieves the following results on the evaluation set:
- Loss: 1.9959
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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.0102 | 1.1111 | 500 | 1.7723 |
| 0.5375 | 2.2222 | 1000 | 1.9768 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.3.0+cu121
- Datasets 3.0.2
- Tokenizers 0.20.3
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