---
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-ES2-0.1
  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/vy4xlg1g)
# qwen2.5-0.5b-expo-DPO-ES2-0.1

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: 0.6808
- Logps: -90.9674
- Logits: -1.6164
- Objective: 0.6836
- Dpo Loss: 0.6836
- Regularize: 0.6836
- Ranking Simple: 0.5331
- Ranking Idealized: 0.6030
- Ranking Idealized Expo: 0.5223
- Wo Beta: 7.8643

## 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: 1e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- gradient_accumulation_steps: 12
- total_train_batch_size: 144
- total_eval_batch_size: 12
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Logps     | Logits  | Objective | Dpo Loss | Regularize | Ranking Simple | Ranking Idealized | Ranking Idealized Expo | Wo Beta |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-----------------:|:----------------------:|:-------:|
| 0.689         | 0.1417 | 50   | 0.6875          | -90.0815  | -1.4869 | 0.6892    | 0.6892   | 0.6892     | 0.5259         | 0.6030            | 0.5223                 | 7.8857  |
| 0.6673        | 0.2834 | 100  | 0.6808          | -90.9674  | -1.6164 | 0.6836    | 0.6836   | 0.6836     | 0.5331         | 0.6030            | 0.5223                 | 7.8643  |
| 0.6376        | 0.4251 | 150  | 0.6785          | -94.6386  | -1.6873 | 0.6833    | 0.6833   | 0.6833     | 0.5342         | 0.6030            | 0.5223                 | 8.1745  |
| 0.5955        | 0.5668 | 200  | 0.6808          | -100.2786 | -1.8583 | 0.6818    | 0.6818   | 0.6818     | 0.5342         | 0.6030            | 0.5223                 | 7.9037  |
| 0.5623        | 0.7085 | 250  | 0.6757          | -97.3034  | -1.9407 | 0.6757    | 0.6757   | 0.6757     | 0.5362         | 0.6030            | 0.5223                 | 7.9161  |
| 0.5255        | 0.8503 | 300  | 0.7037          | -102.4820 | -2.0313 | 0.7119    | 0.7119   | 0.7119     | 0.5352         | 0.6030            | 0.5223                 | 8.7956  |
| 0.4939        | 0.9920 | 350  | 0.6897          | -102.1435 | -1.9358 | 0.6916    | 0.6916   | 0.6916     | 0.5419         | 0.6030            | 0.5223                 | 8.3961  |


### Framework versions

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