---
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-500-5e6
  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/8yjlyly5)
# qwen2.5-0.5b-expo-L2EXPO-EXPERIMENT-500-5e6

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: 2234.1663
- Logps: -82.0980
- Logits: -0.6597
- Objective: 2265.8794
- Dpo Loss: 1141.8063
- Regularize: 2265.8794
- Ranking Simple: 0.5124
- 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: 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:---------:|:----------:|:--------------:|:-----------------:|:----------------------:|
| 737.2396      | 0.2834 | 50   | 421.9188        | -92.0238 | -1.3125 | 428.8152  | 221.7374  | 428.8152   | 0.5093         | 0.5093            | 0.5093                 |
| 1559.0492     | 0.5668 | 100  | 1500.8584       | -82.7953 | -1.0226 | 1492.8041 | 733.0991  | 1492.8041  | 0.5072         | 0.5093            | 0.5093                 |
| 1544.2886     | 0.8503 | 150  | 1796.8794       | -83.3935 | -0.8486 | 1837.2159 | 936.6276  | 1837.2159  | 0.4990         | 0.5093            | 0.5093                 |
| 1387.1779     | 1.1337 | 200  | 1946.6445       | -81.0039 | -0.8010 | 1988.5870 | 1018.1060 | 1988.5870  | 0.5010         | 0.5093            | 0.5093                 |
| 1257.5858     | 1.4171 | 250  | 2056.7834       | -79.5628 | -0.8937 | 2078.7400 | 1059.1973 | 2078.7400  | 0.5031         | 0.5093            | 0.5093                 |
| 1062.9078     | 1.7005 | 300  | 2170.6946       | -79.7273 | -0.7209 | 2202.7805 | 1115.7678 | 2202.7805  | 0.5031         | 0.5093            | 0.5093                 |
| 1015.0369     | 1.9839 | 350  | 2227.1714       | -83.5951 | -0.6739 | 2262.3740 | 1156.4828 | 2262.3740  | 0.5124         | 0.5093            | 0.5093                 |
| 849.8354      | 2.2674 | 400  | 2210.6672       | -83.3996 | -0.6954 | 2238.0188 | 1124.7909 | 2238.0188  | 0.5155         | 0.5093            | 0.5093                 |
| 749.1392      | 2.5508 | 450  | 2232.3298       | -80.8498 | -0.6204 | 2283.4070 | 1157.1035 | 2283.4070  | 0.5134         | 0.5093            | 0.5093                 |
| 663.6063      | 2.8342 | 500  | 2235.3254       | -81.1036 | -0.6463 | 2277.7737 | 1152.4823 | 2277.7737  | 0.5083         | 0.5093            | 0.5093                 |
| 547.2687      | 3.1176 | 550  | 2247.6917       | -81.3519 | -0.6623 | 2265.5049 | 1133.8970 | 2265.5049  | 0.5145         | 0.5093            | 0.5093                 |
| 451.9043      | 3.4010 | 600  | 2235.0491       | -81.8093 | -0.6081 | 2263.8958 | 1143.4464 | 2263.8958  | 0.5114         | 0.5093            | 0.5093                 |
| 383.0005      | 3.6845 | 650  | 2233.3066       | -81.6021 | -0.6417 | 2277.5994 | 1148.9692 | 2277.5994  | 0.5124         | 0.5093            | 0.5093                 |
| 316.0834      | 3.9679 | 700  | 2236.5557       | -82.0739 | -0.6441 | 2269.0681 | 1143.5380 | 2269.0681  | 0.5134         | 0.5093            | 0.5093                 |
| 230.1662      | 4.2513 | 750  | 2241.1863       | -82.1894 | -0.6514 | 2272.5417 | 1146.1786 | 2272.5417  | 0.5124         | 0.5093            | 0.5093                 |
| 198.8015      | 4.5347 | 800  | 2236.1729       | -82.0761 | -0.6625 | 2266.9819 | 1141.6486 | 2266.9819  | 0.5134         | 0.5093            | 0.5093                 |
| 189.8097      | 4.8181 | 850  | 2234.3398       | -82.0995 | -0.6599 | 2266.1760 | 1141.9380 | 2266.1760  | 0.5124         | 0.5093            | 0.5093                 |


### Framework versions

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