---
library_name: peft
license: other
base_model: Qwen/Qwen2.5-Coder-3B
tags:
- llama-factory
- lora
- generated_from_trainer
model-index:
- name: train_2025-04-13-11-42-17
  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_2025-04-13-11-42-17

This model is a fine-tuned version of [Qwen/Qwen2.5-Coder-3B](https://huggingface.co/Qwen/Qwen2.5-Coder-3B) on the hccsri dataset.
It achieves the following results on the evaluation set:
- Loss: 3.0146
- Num Input Tokens Seen: 304528

## 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-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- 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
- num_epochs: 1.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Input Tokens Seen |
|:-------------:|:------:|:----:|:---------------:|:-----------------:|
| 3.3828        | 0.0421 | 100  | 3.3995          | 12336             |
| 3.7301        | 0.0842 | 200  | 3.3119          | 25168             |
| 2.7913        | 0.1263 | 300  | 3.2942          | 38256             |
| 2.9739        | 0.1684 | 400  | 3.2371          | 51344             |
| 2.4265        | 0.2105 | 500  | 3.2291          | 64896             |
| 3.2421        | 0.2526 | 600  | 3.1979          | 77584             |
| 3.1406        | 0.2947 | 700  | 3.1769          | 89952             |
| 3.1426        | 0.3368 | 800  | 3.1570          | 102976            |
| 3.101         | 0.3789 | 900  | 3.1375          | 115536            |
| 3.3436        | 0.4211 | 1000 | 3.1259          | 129104            |
| 3.2059        | 0.4632 | 1100 | 3.0889          | 142176            |
| 3.2607        | 0.5053 | 1200 | 3.0811          | 155360            |
| 2.8431        | 0.5474 | 1300 | 3.0604          | 168080            |
| 3.3622        | 0.5895 | 1400 | 3.0450          | 181424            |
| 2.2921        | 0.6316 | 1500 | 3.0402          | 193696            |
| 3.1937        | 0.6737 | 1600 | 3.0319          | 206800            |
| 3.2635        | 0.7158 | 1700 | 3.0285          | 219920            |
| 2.9374        | 0.7579 | 1800 | 3.0246          | 232224            |
| 3.3592        | 0.8    | 1900 | 3.0196          | 244976            |
| 3.1163        | 0.8421 | 2000 | 3.0173          | 256912            |
| 2.8533        | 0.8842 | 2100 | 3.0168          | 270112            |
| 3.6021        | 0.9263 | 2200 | 3.0151          | 282512            |
| 3.2839        | 0.9684 | 2300 | 3.0146          | 295680            |


### Framework versions

- PEFT 0.15.1
- Transformers 4.51.1
- Pytorch 2.6.0+cu118
- Datasets 3.2.0
- Tokenizers 0.21.0