---
license: apache-2.0
base_model: hZzy/qwen2.5-0.5b-sft-news-IFT
tags:
- trl
- expo
- generated_from_trainer
model-index:
- name: qwen2.5-0.5b-expo-DPO-ES-10
  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/8420vo52)
# qwen2.5-0.5b-expo-DPO-ES-10

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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 21.3539
- Logps: -79.7115
- Logits: -0.5475
- Objective: 20.4532
- Dpo Loss: 20.4532
- Regularize: 20.4532
- Ranking Simple: 0.5362
- Ranking Idealized: 0.5212
- Ranking Idealized Expo: 0.5212
- Wo Beta: 6.6867

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-----------------:|:----------------------:|:-------:|
| 2.0094        | 0.1417 | 50   | 3.1068          | -90.6242 | -1.4592 | 3.0980    | 3.0980   | 3.0980     | 0.5259         | 0.5212            | 0.5212                 | 7.7179  |
| 5.9165        | 0.2834 | 100  | 7.1487          | -82.8335 | -1.4642 | 7.1399    | 7.1399   | 7.1399     | 0.5300         | 0.5212            | 0.5212                 | 7.4498  |
| 9.9617        | 0.4251 | 150  | 11.8998         | -83.0745 | -1.3437 | 11.3536   | 11.3536  | 11.3536    | 0.5305         | 0.5212            | 0.5212                 | 7.2609  |
| 12.4724       | 0.5668 | 200  | 17.0987         | -79.9360 | -1.3880 | 16.0617   | 16.0617  | 16.0617    | 0.5300         | 0.5212            | 0.5212                 | 7.2290  |
| 13.2936       | 0.7085 | 250  | 18.5309         | -77.3150 | -1.3641 | 17.7971   | 17.7971  | 17.7971    | 0.5342         | 0.5212            | 0.5212                 | 7.2078  |
| 11.5204       | 0.8503 | 300  | 19.4344         | -76.9798 | -0.9941 | 18.7017   | 18.7017  | 18.7017    | 0.5357         | 0.5212            | 0.5212                 | 7.0136  |
| 11.3717       | 0.9920 | 350  | 20.3959         | -76.1623 | -1.0426 | 19.0398   | 19.0398  | 19.0398    | 0.5409         | 0.5212            | 0.5212                 | 7.0261  |
| 7.0971        | 1.1337 | 400  | 21.9279         | -76.1458 | -0.6236 | 21.6902   | 21.6902  | 21.6902    | 0.5388         | 0.5212            | 0.5212                 | 7.1227  |
| 7.5725        | 1.2754 | 450  | 20.9480         | -76.3924 | -0.8352 | 20.3853   | 20.3853  | 20.3853    | 0.5373         | 0.5212            | 0.5212                 | 6.8500  |
| 7.6466        | 1.4171 | 500  | 20.9821         | -80.7806 | -0.7483 | 20.2651   | 20.2651  | 20.2651    | 0.5326         | 0.5212            | 0.5212                 | 6.8824  |
| 6.9565        | 1.5588 | 550  | 21.3506         | -80.2051 | -0.6148 | 20.5661   | 20.5661  | 20.5661    | 0.5383         | 0.5212            | 0.5212                 | 6.6513  |
| 6.7183        | 1.7005 | 600  | 21.1265         | -78.5344 | -0.6067 | 20.0027   | 20.0027  | 20.0027    | 0.5367         | 0.5212            | 0.5212                 | 6.6768  |
| 6.9931        | 1.8422 | 650  | 22.2083         | -77.6509 | -0.5872 | 21.4455   | 21.4455  | 21.4455    | 0.5383         | 0.5212            | 0.5212                 | 6.8190  |
| 6.1685        | 1.9839 | 700  | 22.3607         | -77.1493 | -0.5436 | 21.5512   | 21.5512  | 21.5512    | 0.5404         | 0.5212            | 0.5212                 | 6.7299  |
| 3.4811        | 2.1256 | 750  | 21.8349         | -78.9312 | -0.7313 | 21.1379   | 21.1379  | 21.1379    | 0.5424         | 0.5212            | 0.5212                 | 6.8213  |
| 3.3995        | 2.2674 | 800  | 21.3539         | -79.7115 | -0.5475 | 20.4532   | 20.4532  | 20.4532    | 0.5362         | 0.5212            | 0.5212                 | 6.6867  |


### Framework versions

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