|
|
--- |
|
|
library_name: transformers |
|
|
license: other |
|
|
base_model: Qwen/Qwen2.5-Coder-3B-Instruct |
|
|
tags: |
|
|
- llama-factory |
|
|
- full |
|
|
- generated_from_trainer |
|
|
model-index: |
|
|
- name: ex43_qwen2.5_3b_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. --> |
|
|
|
|
|
# ex43_qwen2.5_3b_61k_source_16kcw_2ep_cuda_amd_os |
|
|
|
|
|
This model is a fine-tuned version of [Qwen/Qwen2.5-Coder-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-3B-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: 2 |
|
|
- gradient_accumulation_steps: 8 |
|
|
- total_train_batch_size: 128 |
|
|
- 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_ratio: 0.1 |
|
|
- num_epochs: 2.0 |
|
|
|
|
|
### Training results |
|
|
|
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.46.1 |
|
|
- Pytorch 2.5.1+cu124 |
|
|
- Datasets 3.1.0 |
|
|
- Tokenizers 0.20.3 |
|
|
|
|
|
|
|
|
## 🔗 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) |
