---
library_name: transformers
license: other
base_model: ali-elganzory/Qwen2.5-1.5B-DPO-Tulu3-decontaminated
tags:
- llama-factory
- full
- generated_from_trainer
datasets:
- arrow
model-index:
- name: sft__f679a5c592c8dffb__95711170dd9a2e543373__fa2-qwen-steps
  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. -->

# sft__f679a5c592c8dffb__95711170dd9a2e543373__fa2-qwen-steps

This model is a fine-tuned version of [ali-elganzory/Qwen2.5-1.5B-DPO-Tulu3-decontaminated](https://huggingface.co/ali-elganzory/Qwen2.5-1.5B-DPO-Tulu3-decontaminated) on the /gpfs/scratch/ehpc524/ot/hf_hub/datasets/open-thoughts_open_thoughts3-1.2_m_30000_samples/default/0.0.0/f679a5c592c8dffb 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: 4e-05
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 32
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 256
- 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_ratio: 0.1
- num_epochs: 5.0

### Training results



### Framework versions

- Transformers 4.55.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.4
- Tokenizers 0.21.4
