---
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-L2EXPO-EXPERIMENT-0.05-1e6
  results: []
---

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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/b5meuzz3)
# qwen2.5-0.5b-expo-L2EXPO-EXPERIMENT-0.05-1e6

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: 0.4083
- Logps: -95.9768
- Logits: -1.6921
- Objective: 0.4121
- Dpo Loss: 0.6843
- Regularize: 0.4121
- Ranking Simple: 0.5207
- Ranking Idealized: 0.6570
- Ranking Idealized Expo: 0.5114

## 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: 1e-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: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Logps    | Logits  | Objective | Dpo Loss | Regularize | Ranking Simple | Ranking Idealized | Ranking Idealized Expo |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-----------------:|:----------------------:|
| 0.4009        | 0.2834 | 50   | 0.4077          | -90.3481 | -1.5066 | 0.4091    | 0.6906   | 0.4091     | 0.5145         | 0.6570            | 0.5114                 |
| 0.3456        | 0.5668 | 100  | 0.4037          | -92.6246 | -1.6104 | 0.4081    | 0.6867   | 0.4081     | 0.5207         | 0.6570            | 0.5114                 |
| 0.2786        | 0.8503 | 150  | 0.4061          | -94.6236 | -1.6473 | 0.4131    | 0.6873   | 0.4131     | 0.5207         | 0.6570            | 0.5114                 |
| 0.2075        | 1.1337 | 200  | 0.4085          | -95.7674 | -1.6490 | 0.4120    | 0.6856   | 0.4120     | 0.5176         | 0.6570            | 0.5114                 |
| 0.1852        | 1.4171 | 250  | 0.4045          | -95.1014 | -1.6977 | 0.4080    | 0.6845   | 0.4080     | 0.5227         | 0.6570            | 0.5114                 |
| 0.172         | 1.7005 | 300  | 0.4055          | -95.9442 | -1.6403 | 0.4098    | 0.6843   | 0.4098     | 0.5227         | 0.6570            | 0.5114                 |
| 0.1504        | 1.9839 | 350  | 0.4066          | -96.3838 | -1.6735 | 0.4094    | 0.6840   | 0.4094     | 0.5196         | 0.6570            | 0.5114                 |
| 0.1241        | 2.2674 | 400  | 0.4076          | -95.9834 | -1.6893 | 0.4112    | 0.6844   | 0.4112     | 0.5238         | 0.6570            | 0.5114                 |
| 0.1083        | 2.5508 | 450  | 0.4061          | -96.4275 | -1.6814 | 0.4094    | 0.6838   | 0.4094     | 0.5196         | 0.6570            | 0.5114                 |
| 0.0989        | 2.8342 | 500  | 0.4076          | -95.7645 | -1.6797 | 0.4115    | 0.6844   | 0.4115     | 0.5176         | 0.6570            | 0.5114                 |
| 0.0857        | 3.1176 | 550  | 0.4070          | -96.7057 | -1.6864 | 0.4108    | 0.6841   | 0.4108     | 0.5196         | 0.6570            | 0.5114                 |
| 0.0723        | 3.4010 | 600  | 0.4083          | -96.7714 | -1.6934 | 0.4112    | 0.6840   | 0.4112     | 0.5227         | 0.6570            | 0.5114                 |
| 0.0603        | 3.6845 | 650  | 0.4085          | -95.6858 | -1.6889 | 0.4126    | 0.6846   | 0.4126     | 0.5207         | 0.6570            | 0.5114                 |
| 0.0658        | 3.9679 | 700  | 0.4086          | -95.9264 | -1.6962 | 0.4119    | 0.6843   | 0.4119     | 0.5217         | 0.6570            | 0.5114                 |
| 0.0521        | 4.2513 | 750  | 0.4083          | -95.9188 | -1.6900 | 0.4119    | 0.6843   | 0.4119     | 0.5227         | 0.6570            | 0.5114                 |
| 0.0529        | 4.5347 | 800  | 0.4081          | -95.8100 | -1.6918 | 0.4119    | 0.6843   | 0.4119     | 0.5207         | 0.6570            | 0.5114                 |
| 0.0471        | 4.8181 | 850  | 0.4083          | -95.9782 | -1.6920 | 0.4121    | 0.6844   | 0.4121     | 0.5196         | 0.6570            | 0.5114                 |


### Framework versions

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