---
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-ES-1
  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/zba5f93y)
# qwen2.5-0.5b-expo-DPO-ES-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: 2.3420
- Logps: -83.4105
- Logits: -0.6597
- Objective: 2.2592
- Dpo Loss: 2.2592
- Regularize: 2.2592
- Ranking Simple: 0.5404
- Ranking Idealized: 0.5295
- Ranking Idealized Expo: 0.5212
- Wo Beta: 6.6836

## 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: 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-----------------:|:----------------------:|:-------:|
| 0.7017        | 0.1417 | 50   | 0.8470          | -93.0245 | -1.4582 | 0.8570    | 0.8570   | 0.8570     | 0.5238         | 0.5295            | 0.5212                 | 7.8506  |
| 0.8112        | 0.2834 | 100  | 1.0529          | -86.6804 | -1.4383 | 1.0274    | 1.0274   | 1.0274     | 0.5285         | 0.5295            | 0.5212                 | 7.4982  |
| 1.0895        | 0.4251 | 150  | 1.4498          | -84.4335 | -1.2965 | 1.4010    | 1.4010   | 1.4010     | 0.5321         | 0.5295            | 0.5212                 | 7.2692  |
| 1.2362        | 0.5668 | 200  | 1.7035          | -77.7194 | -1.2955 | 1.6116    | 1.6116   | 1.6116     | 0.5321         | 0.5295            | 0.5212                 | 7.2264  |
| 1.3151        | 0.7085 | 250  | 1.9222          | -92.7224 | -1.2565 | 1.8319    | 1.8319   | 1.8319     | 0.5311         | 0.5295            | 0.5212                 | 7.1855  |
| 1.1899        | 0.8503 | 300  | 2.0297          | -90.9351 | -0.9786 | 1.9587    | 1.9587   | 1.9587     | 0.5367         | 0.5295            | 0.5212                 | 6.9337  |
| 1.1441        | 0.9920 | 350  | 2.1653          | -82.1291 | -1.0211 | 2.0545    | 2.0545   | 2.0545     | 0.5424         | 0.5295            | 0.5212                 | 7.0017  |
| 0.725         | 1.1337 | 400  | 2.2886          | -84.3458 | -0.7529 | 2.2360    | 2.2360   | 2.2360     | 0.5331         | 0.5295            | 0.5212                 | 7.1541  |
| 0.7626        | 1.2754 | 450  | 2.1595          | -80.5955 | -0.8863 | 2.0657    | 2.0657   | 2.0657     | 0.5326         | 0.5295            | 0.5212                 | 6.7939  |
| 0.8048        | 1.4171 | 500  | 2.2134          | -82.3489 | -0.7432 | 2.0975    | 2.0975   | 2.0975     | 0.5342         | 0.5295            | 0.5212                 | 6.7984  |
| 0.7106        | 1.5588 | 550  | 2.1705          | -85.0673 | -0.6665 | 2.0696    | 2.0696   | 2.0696     | 0.5321         | 0.5295            | 0.5212                 | 6.8614  |
| 0.6934        | 1.7005 | 600  | 2.2127          | -81.6773 | -0.7358 | 2.0693    | 2.0693   | 2.0693     | 0.5362         | 0.5295            | 0.5212                 | 6.7265  |
| 0.6885        | 1.8422 | 650  | 2.2198          | -82.8870 | -0.6787 | 2.1432    | 2.1432   | 2.1432     | 0.5362         | 0.5295            | 0.5212                 | 6.8202  |
| 0.6477        | 1.9839 | 700  | 2.3420          | -83.4105 | -0.6597 | 2.2592    | 2.2592   | 2.2592     | 0.5404         | 0.5295            | 0.5212                 | 6.6836  |
| 0.3785        | 2.1256 | 750  | 2.2919          | -84.0369 | -0.7841 | 2.2005    | 2.2005   | 2.2005     | 0.5435         | 0.5295            | 0.5212                 | 6.8514  |
| 0.3316        | 2.2674 | 800  | 2.2220          | -84.2990 | -0.6767 | 2.1123    | 2.1123   | 2.1123     | 0.5409         | 0.5295            | 0.5212                 | 6.7663  |
| 0.3283        | 2.4091 | 850  | 2.3020          | -85.0834 | -0.6538 | 2.2212    | 2.2212   | 2.2212     | 0.5409         | 0.5295            | 0.5212                 | 6.7773  |
| 0.3516        | 2.5508 | 900  | 2.2723          | -84.7564 | -0.6225 | 2.1911    | 2.1911   | 2.1911     | 0.5362         | 0.5295            | 0.5212                 | 6.8162  |
| 0.3245        | 2.6925 | 950  | 2.3304          | -83.6421 | -0.7129 | 2.2523    | 2.2523   | 2.2523     | 0.5336         | 0.5295            | 0.5212                 | 6.8942  |


### Framework versions

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