---
library_name: transformers
license: other
base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: train_2025-01-23-00-42-56
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# train_2025-01-23-00-42-56

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 the smoltalk_chinese dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9459

## 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: 0.0003
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 16
- 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_steps: 100
- num_epochs: 2.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.8719        | 1.7649 | 5000 | 1.9466          |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3

### MISC

```python
_register_template(
    name="deepseekr1",
    default_system="You are a helpful and harmless assistant. You should think step-by-step. Output your thoughts in <think></think> tags.",
    format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
    format_system=StringFormatter(slots=["{{content}}"]),
    format_user=StringFormatter(
        slots=[
            "<｜User｜>{{content}}<｜Assistant｜>"
        ]
    ),
    stop_words=["<｜end▁of▁sentence｜>"],
)
```