---
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-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/yo316k60)
# qwen2.5-0.5b-expo-L2EXPO-EXPERIMENT-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: 5.9301
- Logps: -88.3847
- Logits: -1.2661
- Objective: 5.9752
- Dpo Loss: 3.0906
- Regularize: 5.9752
- Ranking Simple: 0.5134
- Ranking Idealized: 0.5093
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-----------------:|:----------------------:|
| 1.7171        | 0.2834 | 50   | 0.9452          | -91.4216 | -1.3980 | 0.9804    | 0.8391   | 0.9804     | 0.5114         | 0.5093            | 0.5093                 |
| 4.4116        | 0.5668 | 100  | 2.2889          | -91.3584 | -1.3646 | 2.2847    | 1.3937   | 2.2847     | 0.5145         | 0.5093            | 0.5093                 |
| 5.641         | 0.8503 | 150  | 3.6592          | -89.6013 | -1.3612 | 3.6993    | 1.8989   | 3.6993     | 0.5124         | 0.5093            | 0.5093                 |
| 5.6662        | 1.1337 | 200  | 4.9017          | -91.8203 | -1.3129 | 5.1434    | 2.5622   | 5.1434     | 0.5134         | 0.5093            | 0.5093                 |
| 5.0544        | 1.4171 | 250  | 4.6457          | -89.6596 | -1.2958 | 4.6981    | 2.3884   | 4.6981     | 0.5093         | 0.5093            | 0.5093                 |
| 4.799         | 1.7005 | 300  | 5.0697          | -89.6459 | -1.3128 | 5.1481    | 2.5371   | 5.1481     | 0.5114         | 0.5093            | 0.5093                 |
| 4.3968        | 1.9839 | 350  | 5.4045          | -88.5459 | -1.2879 | 5.3636    | 2.7971   | 5.3636     | 0.5103         | 0.5093            | 0.5093                 |
| 3.8148        | 2.2674 | 400  | 5.7626          | -88.2542 | -1.2680 | 5.8200    | 2.9398   | 5.8200     | 0.5093         | 0.5093            | 0.5093                 |
| 3.4169        | 2.5508 | 450  | 5.9539          | -88.0116 | -1.2897 | 6.1065    | 3.1384   | 6.1065     | 0.5145         | 0.5093            | 0.5093                 |
| 2.988         | 2.8342 | 500  | 5.9854          | -87.9506 | -1.2856 | 6.0183    | 3.1318   | 6.0183     | 0.5093         | 0.5093            | 0.5093                 |
| 2.4859        | 3.1176 | 550  | 6.1946          | -88.5030 | -1.2805 | 6.2029    | 3.1790   | 6.2029     | 0.5103         | 0.5093            | 0.5093                 |
| 2.0539        | 3.4010 | 600  | 5.9332          | -88.1616 | -1.2651 | 6.0318    | 3.1111   | 6.0318     | 0.5114         | 0.5093            | 0.5093                 |
| 1.664         | 3.6845 | 650  | 5.9239          | -88.6992 | -1.2608 | 5.9851    | 3.0968   | 5.9851     | 0.5114         | 0.5093            | 0.5093                 |
| 1.3502        | 3.9679 | 700  | 5.9176          | -88.5236 | -1.2647 | 5.9571    | 3.0895   | 5.9571     | 0.5134         | 0.5093            | 0.5093                 |
| 1.0052        | 4.2513 | 750  | 5.9642          | -88.3618 | -1.2630 | 6.0061    | 3.1036   | 6.0061     | 0.5134         | 0.5093            | 0.5093                 |
| 0.8548        | 4.5347 | 800  | 5.9238          | -88.3534 | -1.2662 | 5.9711    | 3.0853   | 5.9711     | 0.5134         | 0.5093            | 0.5093                 |
| 0.7765        | 4.8181 | 850  | 5.9323          | -88.3874 | -1.2660 | 5.9770    | 3.0916   | 5.9770     | 0.5134         | 0.5093            | 0.5093                 |


### Framework versions

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