---
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-0.5-5e6
  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/e9puntse)
# qwen2.5-0.5b-expo-L2EXPO-EXPERIMENT-0.5-5e6

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: 2.2556
- Logps: -80.0690
- Logits: -0.6172
- Objective: 2.2419
- Dpo Loss: 1.3282
- Regularize: 2.2419
- Ranking Simple: 0.5134
- Ranking Idealized: 0.5248
- Ranking Idealized Expo: 0.5093

## 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: 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-----------------:|:----------------------:|
| 0.8081        | 0.2834 | 50   | 0.6652          | -91.9364 | -1.3308 | 0.6722    | 0.7266   | 0.6722     | 0.5124         | 0.5248            | 0.5093                 |
| 1.4482        | 0.5668 | 100  | 1.4160          | -83.3251 | -1.0880 | 1.3662    | 0.9745   | 1.3662     | 0.5093         | 0.5248            | 0.5093                 |
| 1.5063        | 0.8503 | 150  | 1.8403          | -79.4245 | -0.9764 | 1.8307    | 1.1388   | 1.8307     | 0.5155         | 0.5248            | 0.5093                 |
| 1.3427        | 1.1337 | 200  | 1.9411          | -78.0898 | -0.8446 | 1.9042    | 1.1943   | 1.9042     | 0.5124         | 0.5248            | 0.5093                 |
| 1.2385        | 1.4171 | 250  | 2.1004          | -81.0783 | -0.8252 | 2.0780    | 1.2812   | 2.0780     | 0.5072         | 0.5248            | 0.5093                 |
| 1.1013        | 1.7005 | 300  | 2.1954          | -78.5161 | -0.6190 | 2.2003    | 1.3091   | 2.2003     | 0.5124         | 0.5248            | 0.5093                 |
| 0.9795        | 1.9839 | 350  | 2.2001          | -78.2914 | -0.6908 | 2.1850    | 1.2866   | 2.1850     | 0.5093         | 0.5248            | 0.5093                 |
| 0.8853        | 2.2674 | 400  | 2.2679          | -78.5732 | -0.6216 | 2.2619    | 1.3223   | 2.2619     | 0.5134         | 0.5248            | 0.5093                 |
| 0.7605        | 2.5508 | 450  | 2.2655          | -78.2840 | -0.6826 | 2.2744    | 1.3572   | 2.2744     | 0.5145         | 0.5248            | 0.5093                 |
| 0.6709        | 2.8342 | 500  | 2.2688          | -79.7185 | -0.6486 | 2.2578    | 1.3375   | 2.2578     | 0.5186         | 0.5248            | 0.5093                 |
| 0.5302        | 3.1176 | 550  | 2.2598          | -80.1419 | -0.6267 | 2.2430    | 1.3210   | 2.2430     | 0.5196         | 0.5248            | 0.5093                 |
| 0.4552        | 3.4010 | 600  | 2.2547          | -79.9582 | -0.6007 | 2.2379    | 1.3298   | 2.2379     | 0.5124         | 0.5248            | 0.5093                 |
| 0.3981        | 3.6845 | 650  | 2.2549          | -80.1880 | -0.5995 | 2.2397    | 1.3238   | 2.2397     | 0.5155         | 0.5248            | 0.5093                 |
| 0.3178        | 3.9679 | 700  | 2.2616          | -80.4560 | -0.6215 | 2.2539    | 1.3332   | 2.2539     | 0.5134         | 0.5248            | 0.5093                 |
| 0.2213        | 4.2513 | 750  | 2.2620          | -80.1501 | -0.6154 | 2.2499    | 1.3297   | 2.2499     | 0.5134         | 0.5248            | 0.5093                 |
| 0.2032        | 4.5347 | 800  | 2.2583          | -80.1241 | -0.6175 | 2.2455    | 1.3295   | 2.2455     | 0.5134         | 0.5248            | 0.5093                 |
| 0.1935        | 4.8181 | 850  | 2.2561          | -80.0661 | -0.6169 | 2.2424    | 1.3284   | 2.2424     | 0.5134         | 0.5248            | 0.5093                 |


### Framework versions

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