---
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-10-5e6
  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/5jlf70he)
# qwen2.5-0.5b-expo-DPO-EXPERIMENT-10-5e6

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: 15.2566
- Logps: -80.3981
- Logits: -1.0046
- Objective: 15.1445
- Dpo Loss: 15.1445
- Regularize: 15.1445
- Ranking Simple: 0.5134
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-----------------:|:----------------------:|
| 9.5723        | 0.2834 | 50   | 9.2586          | -89.6862 | -1.4979 | 9.6501    | 9.6501   | 9.6501     | 0.5134         | 0.5093            | 0.5093                 |
| 9.8364        | 0.5668 | 100  | 15.5453         | -79.4201 | -1.3475 | 15.5409   | 15.5409  | 15.5409    | 0.5176         | 0.5093            | 0.5093                 |
| 8.8451        | 0.8503 | 150  | 16.6626         | -82.1459 | -1.1122 | 16.5626   | 16.5626  | 16.5626    | 0.5145         | 0.5093            | 0.5093                 |
| 3.8083        | 1.1337 | 200  | 16.0519         | -81.6751 | -1.0874 | 16.3240   | 16.3240  | 16.3240    | 0.5186         | 0.5093            | 0.5093                 |
| 3.6019        | 1.4171 | 250  | 15.8144         | -81.5609 | -0.9933 | 15.7679   | 15.7679  | 15.7679    | 0.5176         | 0.5093            | 0.5093                 |
| 2.1682        | 1.7005 | 300  | 15.3824         | -80.3329 | -1.0036 | 15.2004   | 15.2004  | 15.2004    | 0.5114         | 0.5093            | 0.5093                 |
| 2.703         | 1.9839 | 350  | 15.2566         | -80.3981 | -1.0046 | 15.1445   | 15.1445  | 15.1445    | 0.5134         | 0.5093            | 0.5093                 |


### Framework versions

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