---
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-DPO-ES-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/qhqu3qtk)
# qwen2.5-0.5b-expo-DPO-ES-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 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3243
- Logps: -83.2882
- Logits: -0.6651
- Objective: 2.2471
- Dpo Loss: 2.2471
- Regularize: 2.2471
- Ranking Simple: 0.5378
- Ranking Idealized: 0.5295
- Ranking Idealized Expo: 0.5212
- Wo Beta: 6.6815

## 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: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Logps    | Logits  | Objective | Dpo Loss | Regularize | Ranking Simple | Ranking Idealized | Ranking Idealized Expo | Wo Beta |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-----------------:|:----------------------:|:-------:|
| 0.7017        | 0.1417 | 50   | 0.8470          | -93.0243 | -1.4582 | 0.8570    | 0.8570   | 0.8570     | 0.5238         | 0.5295            | 0.5212                 | 7.8507  |
| 0.8112        | 0.2834 | 100  | 1.0529          | -86.6835 | -1.4382 | 1.0273    | 1.0273   | 1.0273     | 0.5285         | 0.5295            | 0.5212                 | 7.4982  |
| 1.0895        | 0.4251 | 150  | 1.4497          | -84.4337 | -1.2965 | 1.4010    | 1.4010   | 1.4010     | 0.5321         | 0.5295            | 0.5212                 | 7.2692  |
| 1.2363        | 0.5668 | 200  | 1.7035          | -77.7201 | -1.2956 | 1.6116    | 1.6116   | 1.6116     | 0.5321         | 0.5295            | 0.5212                 | 7.2264  |
| 1.3152        | 0.7085 | 250  | 1.9222          | -92.7241 | -1.2565 | 1.8319    | 1.8319   | 1.8319     | 0.5311         | 0.5295            | 0.5212                 | 7.1856  |
| 1.1899        | 0.8503 | 300  | 2.0298          | -90.9373 | -0.9785 | 1.9588    | 1.9588   | 1.9588     | 0.5367         | 0.5295            | 0.5212                 | 6.9336  |
| 1.1443        | 0.9920 | 350  | 2.1654          | -82.1414 | -1.0214 | 2.0541    | 2.0541   | 2.0541     | 0.5435         | 0.5295            | 0.5212                 | 7.0024  |
| 0.725         | 1.1337 | 400  | 2.2884          | -84.2526 | -0.7535 | 2.2360    | 2.2360   | 2.2360     | 0.5336         | 0.5295            | 0.5212                 | 7.1525  |
| 0.7629        | 1.2754 | 450  | 2.1606          | -80.4165 | -0.8866 | 2.0671    | 2.0671   | 2.0671     | 0.5321         | 0.5295            | 0.5212                 | 6.7949  |
| 0.8044        | 1.4171 | 500  | 2.2094          | -82.3927 | -0.7503 | 2.0981    | 2.0981   | 2.0981     | 0.5347         | 0.5295            | 0.5212                 | 6.8050  |
| 0.7105        | 1.5588 | 550  | 2.1697          | -84.9780 | -0.6734 | 2.0733    | 2.0733   | 2.0733     | 0.5321         | 0.5295            | 0.5212                 | 6.8722  |
| 0.6925        | 1.7005 | 600  | 2.1957          | -81.5342 | -0.7411 | 2.0558    | 2.0558   | 2.0558     | 0.5357         | 0.5295            | 0.5212                 | 6.7186  |
| 0.6883        | 1.8422 | 650  | 2.2080          | -82.7303 | -0.6908 | 2.1330    | 2.1330   | 2.1330     | 0.5383         | 0.5295            | 0.5212                 | 6.8081  |
| 0.6486        | 1.9839 | 700  | 2.3243          | -83.2882 | -0.6651 | 2.2471    | 2.2471   | 2.2471     | 0.5378         | 0.5295            | 0.5212                 | 6.6815  |
| 0.3793        | 2.1256 | 750  | 2.2675          | -84.2296 | -0.7879 | 2.1825    | 2.1825   | 2.1825     | 0.5409         | 0.5295            | 0.5212                 | 6.8794  |
| 0.3314        | 2.2674 | 800  | 2.2106          | -84.3675 | -0.6651 | 2.1041    | 2.1041   | 2.1041     | 0.5414         | 0.5295            | 0.5212                 | 6.7463  |
| 0.3301        | 2.4091 | 850  | 2.2964          | -84.8913 | -0.6177 | 2.2221    | 2.2221   | 2.2221     | 0.5388         | 0.5295            | 0.5212                 | 6.8020  |
| 0.3509        | 2.5508 | 900  | 2.2796          | -84.3833 | -0.6097 | 2.2099    | 2.2099   | 2.2099     | 0.5393         | 0.5295            | 0.5212                 | 6.7934  |
| 0.321         | 2.6925 | 950  | 2.3403          | -83.2967 | -0.7158 | 2.2649    | 2.2649   | 2.2649     | 0.5331         | 0.5295            | 0.5212                 | 6.8864  |


### Framework versions

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