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---
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-L1EXPO-ES-0.1
  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/f736bh29)
# qwen2.5-0.5b-expo-L1EXPO-ES-0.1

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: 0.5234
- Logps: -82.5192
- Logits: -0.4757
- Objective: 0.5225
- Dpo Loss: 0.7512
- Regularize: 0.5225
- Ranking Simple: 0.5254
- Ranking Idealized: 0.6030
- Ranking Idealized Expo: 0.5223
- Wo Beta: 14.0055

## 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 | Dpo Loss | Logits  | Logps    | Validation Loss | Objective | Ranking Idealized | Ranking Idealized Expo | Ranking Simple | Regularize | Wo Beta |
|:-------------:|:------:|:----:|:--------:|:-------:|:--------:|:---------------:|:---------:|:-----------------:|:----------------------:|:--------------:|:----------:|:-------:|
| 0.0448        | 0.1417 | 50   | 0.6936   | -1.4299 | -90.3888 | 0.0622          | 0.0621    | 0.6030            | 0.5223                 | 0.5243         | 0.0621     | 16.0768 |
| 0.1716        | 0.2834 | 100  | 0.6982   | -1.3597 | -88.7675 | 0.1556          | 0.1559    | 0.6030            | 0.5223                 | 0.5274         | 0.1559     | 15.9436 |
| 0.2858        | 0.4251 | 150  | 0.7183   | -1.2546 | -79.5067 | 0.2912          | 0.2923    | 0.6030            | 0.5223                 | 0.5228         | 0.2923     | 15.0570 |
| 0.3544        | 0.5668 | 200  | 0.7309   | -0.8432 | -83.8485 | 0.3898          | 0.3890    | 0.6030            | 0.5223                 | 0.5228         | 0.3890     | 14.7122 |
| 0.375         | 0.7085 | 250  | 0.7353   | -0.6734 | -81.2900 | 0.4398          | 0.4375    | 0.6030            | 0.5223                 | 0.5243         | 0.4375     | 14.4729 |
| 0.3592        | 0.8503 | 300  | 0.7348   | -0.5501 | -84.4144 | 0.4422          | 0.4388    | 0.6030            | 0.5223                 | 0.5233         | 0.4388     | 14.4403 |
| 0.3351        | 0.9920 | 350  | 0.7354   | -0.5360 | -82.9375 | 0.4676          | 0.4602    | 0.6030            | 0.5223                 | 0.5342         | 0.4602     | 14.2722 |
| 0.3056        | 1.1337 | 400  | 0.7470   | -0.5686 | -80.5606 | 0.4842          | 0.4804    | 0.6030            | 0.5223                 | 0.5254         | 0.4804     | 14.2812 |
| 0.2932        | 1.2754 | 450  | 0.7439   | -0.5565 | -83.6231 | 0.4805          | 0.4755    | 0.6030            | 0.5223                 | 0.5280         | 0.4755     | 14.4640 |
| 0.2864        | 1.4171 | 500  | 0.7510   | -0.6557 | -82.9178 | 0.4964          | 0.4971    | 0.6030            | 0.5223                 | 0.5274         | 0.4971     | 14.2823 |
| 0.2635        | 1.5588 | 550  | 0.7503   | -0.6184 | -81.1614 | 0.5023          | 0.5043    | 0.6030            | 0.5223                 | 0.5228         | 0.5043     | 14.0632 |
| 0.2561        | 1.7005 | 600  | 0.7487   | -0.5805 | -84.7039 | 0.4980          | 0.4964    | 0.6030            | 0.5223                 | 0.5233         | 0.4964     | 14.3352 |
| 0.2448        | 1.8422 | 650  | 0.7503   | -0.4274 | -83.4629 | 0.5171          | 0.5191    | 0.6030            | 0.5223                 | 0.5233         | 0.5191     | 14.2153 |
| 0.2235        | 1.9839 | 700  | 0.7483   | -0.5057 | -81.7196 | 0.4963          | 0.4949    | 0.6030            | 0.5223                 | 0.5233         | 0.4949     | 14.2026 |
| 0.21          | 2.1256 | 750  | 0.7512   | -0.4757 | -82.5192 | 0.5234          | 0.5225    | 0.6030            | 0.5223                 | 0.5254         | 0.5225     | 14.0055 |
| 0.1988        | 2.2674 | 800  | 0.7496   | -0.5578 | -81.0564 | 0.5140          | 0.5114    | 0.6030            | 0.5223                 | 0.5295         | 0.5114     | 14.1030 |
| 0.1845        | 2.4091 | 850  | 0.7516   | -0.5129 | -82.6326 | 0.5205          | 0.5186    | 0.6030            | 0.5223                 | 0.5311         | 0.5186     | 14.1518 |
| 0.1741        | 2.5508 | 900  | 0.7507   | -0.4790 | -82.9809 | 0.5132          | 0.5118    | 0.6030            | 0.5223                 | 0.5238         | 0.5118     | 14.2459 |
| 0.1659        | 2.6925 | 950  | 0.7500   | -0.4840 | -83.8330 | 0.5189          | 0.5193    | 0.6030            | 0.5223                 | 0.5238         | 0.5193     | 14.3029 |
| 0.1539        | 2.8342 | 1000 | 0.7499   | -0.4671 | -82.8831 | 0.5137          | 0.5127    | 0.6030            | 0.5223                 | 0.5269         | 0.5127     | 14.1925 |
| 0.1445        | 2.9806 | 1050 | 0.5116   | -83.1677| -0.5531  | 0.5112          | 0.7478    | 0.5112            | 0.5248                 | 0.6030         | 0.5223     | 14.2141 |
| 0.1261        | 3.1223 | 1100 | 0.5157   | -83.5954| -0.5488  | 0.5165          | 0.7515    | 0.5165            | 0.5233                 | 0.6030         | 0.5223     | 14.1783 |
| 0.1146        | 3.2641 | 1150 | 0.5175   | -83.4265| -0.5372  | 0.5161          | 0.7487    | 0.5161            | 0.5264                 | 0.6030         | 0.5223     | 14.1956 |
| 0.1076        | 3.4058 | 1200 | 0.5169   | -83.9912| -0.4946  | 0.5160          | 0.7492    | 0.5160            | 0.5274                 | 0.6030         | 0.5223     | 14.1241 |
| 0.0981        | 3.5475 | 1250 | 0.5175   | -83.3791| -0.5087  | 0.5185          | 0.7500    | 0.5185            | 0.5311                 | 0.6030         | 0.5223     | 14.2158 |


### Framework versions

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