---
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-1-5e6
  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/b6qlsezn)
# qwen2.5-0.5b-expo-DPO-EXPERIMENT-1-5e6

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: 1.5850
- Logps: -81.4617
- Logits: -1.1346
- Objective: 1.6058
- Dpo Loss: 1.6058
- Regularize: 1.6058
- Ranking Simple: 0.5217
- Ranking Idealized: 0.5145
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-----------------:|:----------------------:|
| 1.0653        | 0.2834 | 50   | 1.1911          | -88.4918 | -1.4769 | 1.2503    | 1.2503   | 1.2503     | 0.5186         | 0.5145            | 0.5093                 |
| 1.0433        | 0.5668 | 100  | 1.6201          | -82.0376 | -1.4625 | 1.6224    | 1.6224   | 1.6224     | 0.5227         | 0.5145            | 0.5093                 |
| 0.8546        | 0.8503 | 150  | 1.6978          | -82.1610 | -1.2570 | 1.7001    | 1.7001   | 1.7001     | 0.5258         | 0.5145            | 0.5093                 |
| 0.3915        | 1.1337 | 200  | 1.7222          | -81.7287 | -1.2002 | 1.7483    | 1.7483   | 1.7483     | 0.5155         | 0.5145            | 0.5093                 |
| 0.361         | 1.4171 | 250  | 1.6479          | -81.3939 | -1.1553 | 1.6762    | 1.6762   | 1.6762     | 0.5269         | 0.5145            | 0.5093                 |
| 0.2219        | 1.7005 | 300  | 1.5928          | -81.4689 | -1.1283 | 1.6152    | 1.6152   | 1.6152     | 0.5248         | 0.5145            | 0.5093                 |
| 0.2782        | 1.9839 | 350  | 1.5850          | -81.4617 | -1.1346 | 1.6058    | 1.6058   | 1.6058     | 0.5217         | 0.5145            | 0.5093                 |


### Framework versions

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