---
license: apache-2.0
base_model: hZzy/qwen2.5-0.5b-sft-news-IFT
tags:
- alignment-handbook
- ndcg
- trl
- expo
- generated_from_trainer
- trl
- expo
- generated_from_trainer
datasets:
- hZzy/train_pairwise
model-index:
- name: qwen2.5-0.5b-expo-DPO-EXPERIMENT-1W
  results: []
---

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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/zhiyuzha-university-of-florida/huggingface/runs/vdo32atw)
# qwen2.5-0.5b-expo-DPO-EXPERIMENT-1W

This model is a fine-tuned version of [hZzy/qwen2.5-0.5b-sft-news-IFT](https://huggingface.co/hZzy/qwen2.5-0.5b-sft-news-IFT) on the hZzy/train_pairwise dataset.
It achieves the following results on the evaluation set:
- Loss: 12497.9082
- Logps: -80.8773
- Logits: -1.3459
- Objective: 12906.1104
- Dpo Loss: 12906.1104
- Regularize: 12906.1104
- Ranking Simple: 0.5258
- Ranking Idealized: 0.5093
- Ranking Idealized Expo: 0.5093

## 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-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 6
- gradient_accumulation_steps: 12
- total_train_batch_size: 288
- total_eval_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Logps    | Logits  | Objective  | Dpo Loss   | Regularize | Ranking Simple | Ranking Idealized | Ranking Idealized Expo |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:----------:|:----------:|:----------:|:--------------:|:-----------------:|:----------------------:|
| 10470.1625    | 0.2834 | 50   | 11322.9775      | -84.9886 | -1.4586 | 11815.3389 | 11815.3389 | 11815.3389 | 0.5165         | 0.5093            | 0.5093                 |
| 8558.2836     | 0.5668 | 100  | 12877.2754      | -82.3385 | -1.3720 | 13248.5166 | 13248.5166 | 13248.5166 | 0.5176         | 0.5093            | 0.5093                 |
| 7521.95       | 0.8503 | 150  | 12664.2070      | -80.5751 | -1.3556 | 12926.7227 | 12926.7227 | 12926.7227 | 0.5227         | 0.5093            | 0.5093                 |


### Framework versions

- Transformers 4.42.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1