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---
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-L1EXPO-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/3epxudpc)
# qwen2.5-0.5b-expo-L1EXPO-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: 4.8354
- Logps: -80.1753
- Logits: -0.6936
- Objective: 4.8114
- Dpo Loss: 2.5735
- Regularize: 4.8114
- Ranking Simple: 0.5248
- Ranking Idealized: 0.5295
- Ranking Idealized Expo: 0.5212
- Wo Beta: 13.9356
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-----------------:|:----------------------:|:-------:|
| 0.4306 | 0.1417 | 50 | 0.5493 | -90.4264 | -1.4289 | 0.5433 | 0.7632 | 0.5433 | 0.5212 | 0.5295 | 0.5212 | 16.2237 |
| 1.748 | 0.2834 | 100 | 1.6975 | -88.0491 | -1.2535 | 1.6864 | 1.1354 | 1.6864 | 0.5228 | 0.5295 | 0.5212 | 15.6834 |
| 2.8697 | 0.4251 | 150 | 2.9624 | -82.4967 | -1.2524 | 2.8923 | 1.6846 | 2.8923 | 0.5243 | 0.5295 | 0.5212 | 15.1970 |
| 3.5268 | 0.5668 | 200 | 4.0302 | -75.9716 | -0.9581 | 3.9597 | 2.1590 | 3.9597 | 0.5238 | 0.5295 | 0.5212 | 14.5792 |
| 3.7241 | 0.7085 | 250 | 4.2694 | -81.3047 | -0.7680 | 4.2728 | 2.3310 | 4.2728 | 0.5259 | 0.5295 | 0.5212 | 14.5615 |
| 3.6109 | 0.8503 | 300 | 4.4908 | -83.9815 | -0.6388 | 4.4573 | 2.4072 | 4.4573 | 0.5264 | 0.5295 | 0.5212 | 14.3464 |
| 3.36 | 0.9920 | 350 | 4.6586 | -80.7491 | -0.5030 | 4.6212 | 2.4991 | 4.6212 | 0.5212 | 0.5295 | 0.5212 | 14.3467 |
| 3.112 | 1.1337 | 400 | 4.7244 | -82.4974 | -0.5664 | 4.7293 | 2.5403 | 4.7293 | 0.5186 | 0.5295 | 0.5212 | 14.4038 |
| 2.9448 | 1.2754 | 450 | 4.8354 | -80.1753 | -0.6936 | 4.8114 | 2.5735 | 4.8114 | 0.5248 | 0.5295 | 0.5212 | 13.9356 |
| 2.8517 | 1.4171 | 500 | 5.0044 | -80.7676 | -0.5973 | 5.0058 | 2.6782 | 5.0058 | 0.5269 | 0.5295 | 0.5212 | 14.2626 |
| 2.632 | 1.5588 | 550 | 4.8777 | -80.5219 | -0.6149 | 4.8844 | 2.5752 | 4.8844 | 0.5223 | 0.5295 | 0.5212 | 14.1469 |
| 2.5208 | 1.7005 | 600 | 4.9258 | -80.1775 | -0.5875 | 4.9621 | 2.5974 | 4.9621 | 0.5243 | 0.5295 | 0.5212 | 14.2669 |
| 2.4198 | 1.8422 | 650 | 5.0327 | -81.0550 | -0.5441 | 5.0454 | 2.6345 | 5.0454 | 0.5269 | 0.5295 | 0.5212 | 14.2479 |
| 2.2699 | 1.9839 | 700 | 4.9659 | -79.7376 | -0.5594 | 4.9951 | 2.6292 | 4.9951 | 0.5212 | 0.5295 | 0.5212 | 14.1755 |
### Framework versions
- Transformers 4.42.0
- Pytorch 2.3.0+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1
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