---
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-L1EXPO-noES-0.1
  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/uh50oig6)
# qwen2.5-0.5b-expo-L1EXPO-noES-0.1

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: 0.1381
- Logps: -85.9802
- Logits: -1.2306
- Objective: 0.1370
- Dpo Loss: 0.6974
- Regularize: 0.1370
- Ranking Simple: 0.5243
- Ranking Idealized: 0.6025
- Ranking Idealized Expo: 0.5233
- Wo Beta: 15.6347

## 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: 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 | Ranking Idealized | Ranking Idealized Expo | Wo Beta |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-----------------:|:----------------------:|:-------:|
| 0.0351        | 0.1417 | 50   | 0.0221          | -91.2329 | -1.3917 | 0.0224    | 0.6927   | 0.0224     | 0.5212         | 0.6025            | 0.5233                 | 16.2217 |
| 0.0877        | 0.2834 | 100  | 0.0433          | -88.6602 | -1.3863 | 0.0447    | 0.6922   | 0.0447     | 0.5238         | 0.6025            | 0.5233                 | 16.1682 |
| 0.1323        | 0.4251 | 150  | 0.0768          | -90.4377 | -1.3054 | 0.0764    | 0.6956   | 0.0764     | 0.5223         | 0.6025            | 0.5233                 | 16.0034 |
| 0.1427        | 0.5668 | 200  | 0.1032          | -88.3433 | -1.3124 | 0.1017    | 0.6959   | 0.1017     | 0.5223         | 0.6025            | 0.5233                 | 15.9928 |
| 0.1451        | 0.7085 | 250  | 0.1178          | -88.0698 | -1.2854 | 0.1185    | 0.6950   | 0.1185     | 0.5274         | 0.6025            | 0.5233                 | 15.7878 |
| 0.1305        | 0.8503 | 300  | 0.1247          | -86.3312 | -1.2863 | 0.1252    | 0.6961   | 0.1252     | 0.5280         | 0.6025            | 0.5233                 | 15.7668 |
| 0.1407        | 0.9920 | 350  | 0.1314          | -86.4501 | -1.2757 | 0.1310    | 0.6976   | 0.1310     | 0.5223         | 0.6025            | 0.5233                 | 15.6570 |
| 0.1245        | 1.1337 | 400  | 0.1399          | -86.2849 | -1.2418 | 0.1390    | 0.6980   | 0.1390     | 0.5259         | 0.6025            | 0.5233                 | 15.6147 |
| 0.1163        | 1.2754 | 450  | 0.1421          | -85.4828 | -1.2307 | 0.1421    | 0.6985   | 0.1421     | 0.5274         | 0.6025            | 0.5233                 | 15.6128 |
| 0.1071        | 1.4171 | 500  | 0.1382          | -87.2673 | -1.2270 | 0.1376    | 0.6980   | 0.1376     | 0.5285         | 0.6025            | 0.5233                 | 15.6445 |
| 0.1045        | 1.5588 | 550  | 0.1428          | -87.0776 | -1.2327 | 0.1426    | 0.6977   | 0.1426     | 0.5254         | 0.6025            | 0.5233                 | 15.5807 |
| 0.0866        | 1.7005 | 600  | 0.1424          | -85.1926 | -1.2196 | 0.1408    | 0.6965   | 0.1408     | 0.5269         | 0.6025            | 0.5233                 | 15.6603 |
| 0.0847        | 1.8422 | 650  | 0.1380          | -86.1129 | -1.2229 | 0.1356    | 0.6974   | 0.1356     | 0.5243         | 0.6025            | 0.5233                 | 15.6660 |
| 0.071         | 1.9839 | 700  | 0.1420          | -85.2496 | -1.2208 | 0.1405    | 0.6980   | 0.1405     | 0.5254         | 0.6025            | 0.5233                 | 15.6109 |
| 0.0546        | 2.1256 | 750  | 0.1423          | -85.4691 | -1.2233 | 0.1407    | 0.6980   | 0.1407     | 0.5259         | 0.6025            | 0.5233                 | 15.6480 |
| 0.0531        | 2.2674 | 800  | 0.1386          | -86.1368 | -1.2206 | 0.1371    | 0.6981   | 0.1371     | 0.5243         | 0.6025            | 0.5233                 | 15.6234 |
| 0.0444        | 2.4091 | 850  | 0.1395          | -86.0362 | -1.2271 | 0.1382    | 0.6980   | 0.1382     | 0.5238         | 0.6025            | 0.5233                 | 15.6472 |
| 0.0438        | 2.5508 | 900  | 0.1387          | -85.8840 | -1.2296 | 0.1374    | 0.6975   | 0.1374     | 0.5238         | 0.6025            | 0.5233                 | 15.6345 |
| 0.0384        | 2.6925 | 950  | 0.1380          | -85.9590 | -1.2285 | 0.1368    | 0.6975   | 0.1368     | 0.5238         | 0.6025            | 0.5233                 | 15.6425 |
| 0.0375        | 2.8342 | 1000 | 0.1380          | -85.9976 | -1.2305 | 0.1369    | 0.6974   | 0.1369     | 0.5243         | 0.6025            | 0.5233                 | 15.6355 |
| 0.0397        | 2.9759 | 1050 | 0.1381          | -85.9802 | -1.2306 | 0.1370    | 0.6974   | 0.1370     | 0.5243         | 0.6025            | 0.5233                 | 15.6347 |


### Framework versions

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