---
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
- alignment-handbook
- ndcg
- generated_from_trainer
datasets:
- hZzy/train_pairwise
model-index:
- name: qwen2.5-0.5b-expo-DPO-ES-TRY
  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. -->

[<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/jz5qh3m8)
# qwen2.5-0.5b-expo-DPO-ES-TRY

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: 0.6866
- Logps: -91.4116
- Logits: -1.5339
- Objective: 0.6926
- Dpo Loss: 0.6926
- Regularize: 0.6926
- Ranking Simple: 0.5052
- Ranking Idealized: 0.5888
- Ranking Idealized Expo: 0.5093
- Dpo Wo Beta: -0.9551

## 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-07
- 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 | Dpo Loss | Dpo Wo Beta | Logits  | Logps     | Validation Loss | Objective | Ranking Idealized | Ranking Idealized Expo | Ranking Simple | Regularize |
|:-------------:|:------:|:----:|:--------:|:-----------:|:-------:|:---------:|:---------------:|:---------:|:-----------------:|:----------------------:|:--------------:|:----------:|
| 0.672         | 0.2041 | 36   | 0.6926   | -0.9551     | -1.5339 | -91.4116  | 0.6866          | 0.6926    | 0.5888            | 0.5093                 | 0.5052         | 0.6926     |
| 0.6533        | 0.4081 | 72   | 0.6885   | -1.1473     | -1.6311 | -92.4758  | 0.6769          | 0.6885    | 0.5888            | 0.5093                 | 0.5176         | 0.6885     |
| 0.604         | 0.6122 | 108  | 0.6853   | -1.3961     | -1.7691 | -94.0584  | 0.6773          | 0.6853    | 0.5888            | 0.5093                 | 0.5186         | 0.6853     |
| 0.5911        | 0.8162 | 144  | 0.6886   | -1.5153     | -1.8165 | -95.7578  | 0.6775          | 0.6886    | 0.5888            | 0.5093                 | 0.5186         | 0.6886     |
| 0.5482        | 1.0203 | 180  | 0.6859   | -98.1346    | -1.8457 | 0.6998    | 0.6998          | 0.6998    | 0.5238            | 0.5888                 | 0.5093         | -1.8685    |
| 0.5171        | 1.2244 | 216  | 0.6891   | -99.3936    | -1.8859 | 0.7004    | 0.7004          | 0.7004    | 0.5248            | 0.5888                 | 0.5093         | -2.0594    |
| 0.5093        | 1.4284 | 252  | 0.6999   | -102.0847   | -1.8968 | 0.7119    | 0.7119          | 0.7119    | 0.5238            | 0.5888                 | 0.5093         | -2.3165    |
| 0.4986        | 1.6325 | 288  | 0.6981   | -102.1441   | -1.9005 | 0.7090    | 0.7090          | 0.7090    | 0.5279            | 0.5888                 | 0.5093         | -2.2741    |
| 0.5055        | 1.8366 | 324  | 0.6965   | -101.5796   | -1.8981 | 0.7080    | 0.7080          | 0.7080    | 0.5279            | 0.5888                 | 0.5093         | -2.2649    |


### Framework versions

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