---
library_name: peft
license: other
base_model: /root/autodl-fs/Qwen2.5-7B-Instruct
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: stage1_cap_func
  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. -->

# stage1_cap_func

This model is a fine-tuned version of [/root/autodl-fs/Qwen2.5-7B-Instruct](https://huggingface.co//root/autodl-fs/Qwen2.5-7B-Instruct) on the textui-caption2k and the textui-function6k datasets.
It achieves the following results on the evaluation set:
- Loss: 0.4610

## 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: 3
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 96
- 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: 25
- training_steps: 250

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.6383        | 0.2436 | 25   | 0.6979          |
| 0.5722        | 0.4872 | 50   | 0.6059          |
| 0.5268        | 0.7308 | 75   | 0.5485          |
| 0.492         | 0.9744 | 100  | 0.5159          |
| 0.4719        | 1.2241 | 125  | 0.4990          |
| 0.4031        | 1.4677 | 150  | 0.4809          |
| 0.3825        | 1.7113 | 175  | 0.4702          |
| 0.3944        | 1.9549 | 200  | 0.4625          |
| 0.3411        | 2.2046 | 225  | 0.4616          |
| 0.3588        | 2.4482 | 250  | 0.4610          |


### Framework versions

- PEFT 0.15.1
- Transformers 4.51.3
- Pytorch 2.7.0+cu126
- Datasets 3.5.0
- Tokenizers 0.21.1