---
library_name: transformers
license: other
base_model: Qwen/Qwen2.5-3B-Instruct
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: qwen2.5-3b-instruct
  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. -->

# qwen2.5-3b-instruct

This model is a fine-tuned version of [Qwen/Qwen2.5-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct) on the codealpaca_train_20k_no_trace_generation dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4735

## 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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 128
- total_train_batch_size: 256
- total_eval_batch_size: 2
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.4377        | 0.7111 | 50   | 0.4685          |
| 0.4175        | 1.4124 | 100  | 0.4669          |
| 0.3545        | 2.1138 | 150  | 0.4679          |
| 0.3659        | 2.8249 | 200  | 0.4734          |


### Framework versions

- Transformers 5.2.0
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2