---
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-1K-5e6
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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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/lxeilq1n)
# qwen2.5-0.5b-expo-DPO-EXPERIMENT-1K-5e6

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: 1521.1873
- Logps: -79.1168
- Logits: -1.0707
- Objective: 1520.4889
- Dpo Loss: 1520.4889
- Regularize: 1520.4889
- 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: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Logps    | Logits  | Objective | Dpo Loss  | Regularize | Ranking Simple | Ranking Idealized | Ranking Idealized Expo |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:---------:|:----------:|:--------------:|:-----------------:|:----------------------:|
| 932.0532      | 0.2834 | 50   | 928.5909        | -90.5890 | -1.5321 | 972.7211  | 972.7211  | 972.7211   | 0.5103         | 0.5093            | 0.5093                 |
| 1035.9887     | 0.5668 | 100  | 1589.5358       | -80.1508 | -1.3577 | 1629.7952 | 1629.7952 | 1629.7952  | 0.5145         | 0.5093            | 0.5093                 |
| 835.8459      | 0.8503 | 150  | 1554.2150       | -79.1304 | -1.1902 | 1554.7245 | 1554.7245 | 1554.7245  | 0.5238         | 0.5093            | 0.5093                 |
| 353.4232      | 1.1337 | 200  | 1601.4404       | -77.8605 | -1.1493 | 1618.9882 | 1618.9882 | 1618.9882  | 0.5279         | 0.5093            | 0.5093                 |
| 363.333       | 1.4171 | 250  | 1571.6953       | -78.8053 | -1.0661 | 1577.6245 | 1577.6245 | 1577.6245  | 0.5227         | 0.5093            | 0.5093                 |
| 267.0769      | 1.7005 | 300  | 1533.1350       | -79.3922 | -1.0587 | 1538.6410 | 1538.6410 | 1538.6410  | 0.5227         | 0.5093            | 0.5093                 |
| 287.4463      | 1.9839 | 350  | 1521.1865       | -79.1168 | -1.0707 | 1520.4884 | 1520.4884 | 1520.4884  | 0.5258         | 0.5093            | 0.5093                 |


### Framework versions

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