---
library_name: transformers
license: other
base_model: Qwen/Qwen2.5-Coder-7B-Instruct
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: 2and3_apps_30k_v6
  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. -->

# 2and3_apps_30k_v6

This model is a fine-tuned version of [Qwen/Qwen2.5-Coder-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct) on the 2and3_apps_30k_v6 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1605

## 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: 5e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- total_eval_batch_size: 4
- 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
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.1745        | 0.1025 | 100  | 0.1826          |
| 0.1915        | 0.2049 | 200  | 0.1744          |
| 0.1889        | 0.3074 | 300  | 0.1699          |
| 0.203         | 0.4098 | 400  | 0.1674          |
| 0.1834        | 0.5123 | 500  | 0.1656          |
| 0.1807        | 0.6148 | 600  | 0.1633          |
| 0.1853        | 0.7172 | 700  | 0.1625          |
| 0.173         | 0.8197 | 800  | 0.1614          |
| 0.1793        | 0.9221 | 900  | 0.1606          |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.6.0+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3