---
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-0.005-5e6
  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/3gvck2ki)
# qwen2.5-0.5b-expo-L2EXPO-EXPERIMENT-0.005-5e6

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: 0.3951
- Logps: -195.4572
- Logits: -3.2699
- Objective: 0.3956
- Dpo Loss: 0.6771
- Regularize: 0.3956
- Ranking Simple: 0.5661
- Ranking Idealized: 0.9194
- Ranking Idealized Expo: 0.5310

## 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 |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-----------------:|:----------------------:|
| 0.4052        | 0.2834 | 50   | 0.4107          | -129.0883 | -1.8292 | 0.4120    | 0.6914   | 0.4120     | 0.5372         | 0.9194            | 0.5310                 |
| 0.3407        | 0.5668 | 100  | 0.4017          | -173.3319 | -2.5066 | 0.4063    | 0.6839   | 0.4063     | 0.5548         | 0.9194            | 0.5310                 |
| 0.2596        | 0.8503 | 150  | 0.4017          | -188.6395 | -2.4464 | 0.4052    | 0.6806   | 0.4052     | 0.5424         | 0.9194            | 0.5310                 |
| 0.1965        | 1.1337 | 200  | 0.4002          | -193.1247 | -2.5977 | 0.4041    | 0.6801   | 0.4041     | 0.5589         | 0.9194            | 0.5310                 |
| 0.1784        | 1.4171 | 250  | 0.3990          | -189.4701 | -2.7528 | 0.4023    | 0.6802   | 0.4023     | 0.5620         | 0.9194            | 0.5310                 |
| 0.1717        | 1.7005 | 300  | 0.4021          | -195.7304 | -2.8777 | 0.4042    | 0.6799   | 0.4042     | 0.5455         | 0.9194            | 0.5310                 |
| 0.1527        | 1.9839 | 350  | 0.3960          | -211.6068 | -3.1101 | 0.3970    | 0.6760   | 0.3970     | 0.5558         | 0.9194            | 0.5310                 |
| 0.1267        | 2.2674 | 400  | 0.3981          | -201.0368 | -3.2515 | 0.3998    | 0.6776   | 0.3998     | 0.5620         | 0.9194            | 0.5310                 |
| 0.1121        | 2.5508 | 450  | 0.3957          | -192.7809 | -2.9523 | 0.3976    | 0.6782   | 0.3976     | 0.5620         | 0.9194            | 0.5310                 |
| 0.1063        | 2.8342 | 500  | 0.3941          | -195.7920 | -3.2835 | 0.3949    | 0.6760   | 0.3949     | 0.5671         | 0.9194            | 0.5310                 |
| 0.0891        | 3.1176 | 550  | 0.3956          | -196.1659 | -3.1953 | 0.3960    | 0.6777   | 0.3960     | 0.5610         | 0.9194            | 0.5310                 |
| 0.0749        | 3.4010 | 600  | 0.3962          | -194.1237 | -3.1966 | 0.3973    | 0.6781   | 0.3973     | 0.5744         | 0.9194            | 0.5310                 |
| 0.062         | 3.6845 | 650  | 0.3956          | -195.3244 | -3.2412 | 0.3967    | 0.6778   | 0.3967     | 0.5702         | 0.9194            | 0.5310                 |
| 0.0583        | 3.9679 | 700  | 0.3956          | -196.4469 | -3.2432 | 0.3961    | 0.6772   | 0.3961     | 0.5640         | 0.9194            | 0.5310                 |
| 0.0451        | 4.2513 | 750  | 0.3952          | -195.4398 | -3.2666 | 0.3955    | 0.6771   | 0.3955     | 0.5671         | 0.9194            | 0.5310                 |
| 0.0438        | 4.5347 | 800  | 0.3952          | -195.2319 | -3.2693 | 0.3956    | 0.6771   | 0.3956     | 0.5661         | 0.9194            | 0.5310                 |
| 0.0408        | 4.8181 | 850  | 0.3951          | -195.5095 | -3.2704 | 0.3956    | 0.6771   | 0.3956     | 0.5661         | 0.9194            | 0.5310                 |


### Framework versions

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