---
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-0.5-1e6
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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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/fbqhf9yl)
# qwen2.5-0.5b-expo-L2EXPO-EXPERIMENT-0.5-1e6

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: 0.7095
- Logps: -87.7114
- Logits: -1.2689
- Objective: 0.7117
- Dpo Loss: 0.7514
- Regularize: 0.7117
- Ranking Simple: 0.5124
- 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: 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-----------------:|:----------------------:|
| 0.3563        | 0.2834 | 50   | 0.4211          | -92.3339 | -1.4209 | 0.4280    | 0.6873   | 0.4280     | 0.5114         | 0.5248            | 0.5093                 |
| 0.4749        | 0.5668 | 100  | 0.4673          | -91.3111 | -1.3982 | 0.4712    | 0.6958   | 0.4712     | 0.5145         | 0.5248            | 0.5093                 |
| 0.5468        | 0.8503 | 150  | 0.5596          | -91.0759 | -1.3204 | 0.5683    | 0.7061   | 0.5683     | 0.5145         | 0.5248            | 0.5093                 |
| 0.5501        | 1.1337 | 200  | 0.6048          | -89.7055 | -1.3004 | 0.5995    | 0.7155   | 0.5995     | 0.5062         | 0.5248            | 0.5093                 |
| 0.5045        | 1.4171 | 250  | 0.6191          | -88.7256 | -1.3194 | 0.6397    | 0.7337   | 0.6397     | 0.5176         | 0.5248            | 0.5093                 |
| 0.5191        | 1.7005 | 300  | 0.6502          | -87.6189 | -1.3167 | 0.6544    | 0.7342   | 0.6544     | 0.5165         | 0.5248            | 0.5093                 |
| 0.4473        | 1.9839 | 350  | 0.6869          | -88.6205 | -1.3002 | 0.6878    | 0.7476   | 0.6878     | 0.5093         | 0.5248            | 0.5093                 |
| 0.3926        | 2.2674 | 400  | 0.7087          | -87.7933 | -1.2740 | 0.7147    | 0.7519   | 0.7147     | 0.5114         | 0.5248            | 0.5093                 |
| 0.3583        | 2.5508 | 450  | 0.6997          | -87.7180 | -1.2638 | 0.7073    | 0.7468   | 0.7073     | 0.5093         | 0.5248            | 0.5093                 |
| 0.2969        | 2.8342 | 500  | 0.7206          | -87.5993 | -1.2820 | 0.7300    | 0.7570   | 0.7300     | 0.5134         | 0.5248            | 0.5093                 |
| 0.2456        | 3.1176 | 550  | 0.7082          | -87.4857 | -1.2747 | 0.7095    | 0.7502   | 0.7095     | 0.5134         | 0.5248            | 0.5093                 |
| 0.2121        | 3.4010 | 600  | 0.7150          | -87.8251 | -1.2611 | 0.7195    | 0.7513   | 0.7195     | 0.5124         | 0.5248            | 0.5093                 |
| 0.1721        | 3.6845 | 650  | 0.7181          | -87.5542 | -1.2667 | 0.7210    | 0.7529   | 0.7210     | 0.5124         | 0.5248            | 0.5093                 |
| 0.1386        | 3.9679 | 700  | 0.7065          | -87.5438 | -1.2654 | 0.7094    | 0.7514   | 0.7094     | 0.5114         | 0.5248            | 0.5093                 |
| 0.0985        | 4.2513 | 750  | 0.7096          | -87.6431 | -1.2699 | 0.7118    | 0.7509   | 0.7118     | 0.5145         | 0.5248            | 0.5093                 |
| 0.0882        | 4.5347 | 800  | 0.7119          | -87.7428 | -1.2693 | 0.7145    | 0.7520   | 0.7145     | 0.5114         | 0.5248            | 0.5093                 |
| 0.0796        | 4.8181 | 850  | 0.7095          | -87.7155 | -1.2689 | 0.7118    | 0.7515   | 0.7118     | 0.5124         | 0.5248            | 0.5093                 |


### Framework versions

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