---
library_name: transformers
license: apache-2.0
base_model: Qwen/Qwen2.5-Coder-1.5B-Instruct
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: ex45_qwen2.5_1.5b_61k_source_16kcw_2ep_cuda_amd_os
  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. -->

# ex45_qwen2.5_1.5b_61k_source_16kcw_2ep_cuda_amd_os

This model is a fine-tuned version of [Qwen/Qwen2.5-Coder-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-1.5B-Instruct) on the cuda_61k_source dataset.

## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- total_eval_batch_size: 32
- 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_ratio: 0.1
- num_epochs: 2.0

### Training results



### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0

## 🔗 Useful Links

* 🤗 Hugging Face Collection: [CASS on Hugging Face](https://huggingface.co/collections/MBZUAI/cass-6825b5bf7414503cf16f87b2)
* 📂 Code & Tools: [GitHub Repository](https://github.com/GustavoStahl/CASS)
* Paper: [Arxiv CASS](https://arxiv.org/abs/2505.16968)