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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-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/zba5f93y)
# 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: 2.3420
- Logps: -83.4105
- Logits: -0.6597
- Objective: 2.2592
- Dpo Loss: 2.2592
- Regularize: 2.2592
- Ranking Simple: 0.5404
- Ranking Idealized: 0.5295
- Ranking Idealized Expo: 0.5212
- Wo Beta: 6.6836
## 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 | -93.0245 | -1.4582 | 0.8570 | 0.8570 | 0.8570 | 0.5238 | 0.5295 | 0.5212 | 7.8506 |
| 0.8112 | 0.2834 | 100 | 1.0529 | -86.6804 | -1.4383 | 1.0274 | 1.0274 | 1.0274 | 0.5285 | 0.5295 | 0.5212 | 7.4982 |
| 1.0895 | 0.4251 | 150 | 1.4498 | -84.4335 | -1.2965 | 1.4010 | 1.4010 | 1.4010 | 0.5321 | 0.5295 | 0.5212 | 7.2692 |
| 1.2362 | 0.5668 | 200 | 1.7035 | -77.7194 | -1.2955 | 1.6116 | 1.6116 | 1.6116 | 0.5321 | 0.5295 | 0.5212 | 7.2264 |
| 1.3151 | 0.7085 | 250 | 1.9222 | -92.7224 | -1.2565 | 1.8319 | 1.8319 | 1.8319 | 0.5311 | 0.5295 | 0.5212 | 7.1855 |
| 1.1899 | 0.8503 | 300 | 2.0297 | -90.9351 | -0.9786 | 1.9587 | 1.9587 | 1.9587 | 0.5367 | 0.5295 | 0.5212 | 6.9337 |
| 1.1441 | 0.9920 | 350 | 2.1653 | -82.1291 | -1.0211 | 2.0545 | 2.0545 | 2.0545 | 0.5424 | 0.5295 | 0.5212 | 7.0017 |
| 0.725 | 1.1337 | 400 | 2.2886 | -84.3458 | -0.7529 | 2.2360 | 2.2360 | 2.2360 | 0.5331 | 0.5295 | 0.5212 | 7.1541 |
| 0.7626 | 1.2754 | 450 | 2.1595 | -80.5955 | -0.8863 | 2.0657 | 2.0657 | 2.0657 | 0.5326 | 0.5295 | 0.5212 | 6.7939 |
| 0.8048 | 1.4171 | 500 | 2.2134 | -82.3489 | -0.7432 | 2.0975 | 2.0975 | 2.0975 | 0.5342 | 0.5295 | 0.5212 | 6.7984 |
| 0.7106 | 1.5588 | 550 | 2.1705 | -85.0673 | -0.6665 | 2.0696 | 2.0696 | 2.0696 | 0.5321 | 0.5295 | 0.5212 | 6.8614 |
| 0.6934 | 1.7005 | 600 | 2.2127 | -81.6773 | -0.7358 | 2.0693 | 2.0693 | 2.0693 | 0.5362 | 0.5295 | 0.5212 | 6.7265 |
| 0.6885 | 1.8422 | 650 | 2.2198 | -82.8870 | -0.6787 | 2.1432 | 2.1432 | 2.1432 | 0.5362 | 0.5295 | 0.5212 | 6.8202 |
| 0.6477 | 1.9839 | 700 | 2.3420 | -83.4105 | -0.6597 | 2.2592 | 2.2592 | 2.2592 | 0.5404 | 0.5295 | 0.5212 | 6.6836 |
| 0.3785 | 2.1256 | 750 | 2.2919 | -84.0369 | -0.7841 | 2.2005 | 2.2005 | 2.2005 | 0.5435 | 0.5295 | 0.5212 | 6.8514 |
| 0.3316 | 2.2674 | 800 | 2.2220 | -84.2990 | -0.6767 | 2.1123 | 2.1123 | 2.1123 | 0.5409 | 0.5295 | 0.5212 | 6.7663 |
| 0.3283 | 2.4091 | 850 | 2.3020 | -85.0834 | -0.6538 | 2.2212 | 2.2212 | 2.2212 | 0.5409 | 0.5295 | 0.5212 | 6.7773 |
| 0.3516 | 2.5508 | 900 | 2.2723 | -84.7564 | -0.6225 | 2.1911 | 2.1911 | 2.1911 | 0.5362 | 0.5295 | 0.5212 | 6.8162 |
| 0.3245 | 2.6925 | 950 | 2.3304 | -83.6421 | -0.7129 | 2.2523 | 2.2523 | 2.2523 | 0.5336 | 0.5295 | 0.5212 | 6.8942 |
### Framework versions
- Transformers 4.42.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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