---
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_weighted
model-index:
- name: qwen2.5-0.5b-expo-DPO-noES4-1
  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/ijq21amu)
# qwen2.5-0.5b-expo-DPO-noES4-1

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_weighted dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0126
- Logps: -79.3398
- Logits: -0.6948
- Objective: 1.9384
- Dpo Loss: 1.9384
- Regularize: 1.9384
- Ranking Simple: 0.5430
- Wo Beta: 6.8782

## 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: 3
- gradient_accumulation_steps: 12
- total_train_batch_size: 144
- total_eval_batch_size: 12
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Logps    | Logits  | Objective | Dpo Loss | Regularize | Ranking Simple | Wo Beta |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-------:|
| 0.9504        | 0.1417 | 50   | 0.9836          | -92.0961 | -1.4075 | 0.9764    | 0.9764   | 0.9764     | 0.5259         | 7.7454  |
| 1.2453        | 0.2834 | 100  | 1.2755          | -89.9832 | -1.3843 | 1.2122    | 1.2122   | 1.2122     | 0.5336         | 7.3870  |
| 1.4306        | 0.4251 | 150  | 1.7989          | -76.2439 | -1.2411 | 1.7433    | 1.7433   | 1.7433     | 0.5357         | 7.2217  |
| 1.3076        | 0.5668 | 200  | 1.9202          | -74.0915 | -1.1859 | 1.8276    | 1.8276   | 1.8276     | 0.5388         | 7.0633  |
| 1.3919        | 0.7085 | 250  | 2.0724          | -78.0833 | -1.1719 | 2.0197    | 2.0197   | 2.0197     | 0.5331         | 7.1561  |
| 1.1295        | 0.8503 | 300  | 2.0572          | -82.8187 | -0.9338 | 1.9944    | 1.9944   | 1.9944     | 0.5404         | 6.9967  |
| 0.9469        | 0.9920 | 350  | 2.1175          | -81.5331 | -0.9147 | 1.9927    | 1.9927   | 1.9927     | 0.5383         | 6.8160  |
| 0.6125        | 1.1337 | 400  | 2.2348          | -81.9750 | -0.7963 | 2.1620    | 2.1620   | 2.1620     | 0.5342         | 6.9279  |
| 0.5932        | 1.2754 | 450  | 2.0919          | -81.2039 | -0.8203 | 2.0152    | 2.0152   | 2.0152     | 0.5378         | 6.8450  |
| 0.6283        | 1.4171 | 500  | 2.1655          | -82.7384 | -0.6531 | 2.0804    | 2.0804   | 2.0804     | 0.5393         | 6.7975  |
| 0.5148        | 1.5588 | 550  | 2.0636          | -83.5332 | -0.7097 | 1.9877    | 1.9877   | 1.9877     | 0.5352         | 6.7990  |
| 0.3647        | 1.7005 | 600  | 2.0351          | -80.1348 | -0.6773 | 1.9649    | 1.9649   | 1.9649     | 0.5373         | 6.8458  |
| 0.5325        | 1.8422 | 650  | 2.0596          | -80.1766 | -0.6632 | 1.9878    | 1.9878   | 1.9878     | 0.5419         | 6.8518  |
| 0.3442        | 1.9839 | 700  | 2.0875          | -80.5005 | -0.6144 | 1.9977    | 1.9977   | 1.9977     | 0.5435         | 6.7884  |
| 0.119         | 2.1256 | 750  | 2.0463          | -80.5714 | -0.6875 | 1.9523    | 1.9523   | 1.9523     | 0.5445         | 6.8488  |
| 0.1373        | 2.2674 | 800  | 2.0092          | -80.3873 | -0.6842 | 1.9315    | 1.9315   | 1.9315     | 0.5461         | 6.8647  |
| 0.131         | 2.4091 | 850  | 2.0060          | -80.0760 | -0.6729 | 1.9353    | 1.9353   | 1.9353     | 0.5450         | 6.8928  |
| 0.1325        | 2.5508 | 900  | 2.0058          | -79.8102 | -0.6821 | 1.9324    | 1.9324   | 1.9324     | 0.5450         | 6.8844  |
| 0.138         | 2.6925 | 950  | 2.0122          | -79.3969 | -0.6917 | 1.9363    | 1.9363   | 1.9363     | 0.5435         | 6.8712  |
| 0.1283        | 2.8342 | 1000 | 2.0122          | -79.3139 | -0.6959 | 1.9376    | 1.9376   | 1.9376     | 0.5430         | 6.8769  |
| 0.0938        | 2.9759 | 1050 | 2.0126          | -79.3398 | -0.6948 | 1.9384    | 1.9384   | 1.9384     | 0.5430         | 6.8782  |


### Framework versions

- Transformers 4.42.0
- Pytorch 2.3.0+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1