---
library_name: transformers
license: other
base_model: Qwen/Qwen2.5-7B
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: qwen7b_full_sft_8gpu_s13
  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. -->

# qwen7b_full_sft_8gpu_s13

This model is a fine-tuned version of [Qwen/Qwen2.5-7B](https://huggingface.co/Qwen/Qwen2.5-7B) on the assimilation_strict_json_v2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 2
- seed: 13
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Use OptimizerNames.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: 0.05
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.0000        | 0.6711 | 50   | 0.0000          |
| 0.0000        | 1.3356 | 100  | 0.0000          |
| 0.0000        | 2.0    | 150  | 0.0000          |
| 0.0000        | 2.6711 | 200  | 0.0000          |
| 0.0000        | 3.0    | 225  | 0.0000          |


### Framework versions

- Transformers 5.6.0
- Pytorch 2.7.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2