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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
- 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/rg2tu2w0)
# 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: 0.8143
- Logps: -120.0593
- Logits: -2.4478
- Objective: 0.8312
- Dpo Loss: 0.8312
- Regularize: 0.8312
- Ranking Simple: 0.5839
- Ranking Idealized: 0.6046
- Ranking Idealized Expo: 0.5280
- Dpo Wo Beta: -5.3609

## 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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 6
- gradient_accumulation_steps: 6
- total_train_batch_size: 72
- 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: 3

### Training results

| Training Loss | Epoch  | Step | Dpo Loss | Dpo Wo Beta | Logits  | Logps     | Validation Loss | Objective | Ranking Idealized | Ranking Idealized Expo | Ranking Simple | Regularize |
|:-------------:|:------:|:----:|:--------:|:-----------:|:-------:|:---------:|:---------------:|:---------:|:-----------------:|:----------------------:|:--------------:|:----------:|
| 0.5954        | 0.3004 | 53   | 0.7113   | -2.2659     | -1.8928 | -101.3674 | 0.6816          | 0.7113    | 0.5888            | 0.5093                 | 0.5238         | 0.7113     |
| 0.4618        | 0.6009 | 106  | 0.6936   | -2.4624     | -1.9007 | -94.3571  | 0.6913          | 0.6936    | 0.5888            | 0.5093                 | 0.5351         | 0.6936     |
| 0.3986        | 0.9013 | 159  | 0.7215   | -3.1229     | -2.1450 | -95.6001  | 0.7014          | 0.7215    | 0.5888            | 0.5093                 | 0.5351         | 0.7215     |
| 0.2551        | 1.2017 | 212  | 0.7525   | -3.7750     | -2.2678 | -98.1427  | 0.7351          | 0.7525    | 0.5888            | 0.5093                 | 0.5372         | 0.7525     |
| 0.2623        | 1.5021 | 265  | 0.7739   | -4.1634     | -2.1478 | -100.8313 | 0.7400          | 0.7739    | 0.5888            | 0.5093                 | 0.5393         | 0.7739     |
| 0.2571        | 1.8026 | 318  | 0.7665   | -4.0950     | -1.9888 | -102.3712 | 0.7401          | 0.7665    | 0.5888            | 0.5093                 | 0.5393         | 0.7665     |
| 0.1227        | 2.1030 | 371  | 0.9224   | -6.4510     | -1.8645 | -122.0016 | 0.8844          | 0.9224    | 0.5888            | 0.5093                 | 0.5424         | 0.9224     |
| 0.133         | 2.4034 | 424  | 0.8786   | -5.8878     | -2.0277 | -117.1217 | 0.8448          | 0.8786    | 0.5888            | 0.5093                 | 0.5413         | 0.8786     |
| 0.1211        | 2.7085 | 477  | 0.8739   | -5.8152     | -2.0272 | -116.4230 | 0.8371          | 0.8739    | 0.5888            | 0.5093                 | 0.5403         | 0.8739     |
| 0.0858        | 1.5045 | 530  | 0.8753   | -5.9229     | -2.4530 | -118.2529 | 0.8505          | 0.8753    | 0.6046            | 0.5280                 | 0.5683         | 0.8753     |
| 0.1274        | 1.6547 | 583  | 0.8264   | -5.2847     | -2.4380 | -119.5907 | 0.8086          | 0.8264    | 0.6046            | 0.5280                 | 0.5870         | 0.8264     |
| 0.1614        | 1.8049 | 636  | 0.8243   | -5.2813     | -2.4850 | -117.8585 | 0.8209          | 0.8243    | 0.6046            | 0.5280                 | 0.5818         | 0.8243     |
| 0.1616        | 1.9551 | 689  | 0.8576   | -5.7234     | -2.4656 | -119.3221 | 0.8383          | 0.8576    | 0.6046            | 0.5280                 | 0.5797         | 0.8576     |
| 0.1063        | 2.1053 | 742  | 0.9824   | -7.3310     | -2.2712 | -133.3637 | 0.9486          | 0.9824    | 0.6046            | 0.5280                 | 0.5518         | 0.9824     |
| 0.1017        | 2.2556 | 795  | 0.8904   | -6.2055     | -2.4490 | -123.5745 | 0.8711          | 0.8904    | 0.6046            | 0.5280                 | 0.5683         | 0.8904     |
| 0.1225        | 2.4058 | 848  | 0.9035   | -6.3529     | -2.4743 | -124.5336 | 0.8822          | 0.9035    | 0.6046            | 0.5280                 | 0.5569         | 0.9035     |
| 0.1157        | 2.5583 | 901  | 0.8718   | -124.4583   | -2.4886 | 0.8941    | 0.8941          | 0.8941    | 0.5621            | 0.6046                 | 0.5280         | -6.2136    |
| 0.1387        | 2.7085 | 954  | 0.8688   | -123.4143   | -2.5086 | 0.8892    | 0.8892          | 0.8892    | 0.5580            | 0.6046                 | 0.5280         | -6.1610    |
| 0.1219        | 2.8588 | 1007 | 0.8682   | -123.1454   | -2.5127 | 0.8882    | 0.8882          | 0.8882    | 0.5600            | 0.6046                 | 0.5280         | -6.1537    |


### Framework versions

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