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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
- alignment-handbook
- ndcg
- generated_from_trainer
datasets:
- hZzy/train_pairwise
model-index:
- name: qwen2.5-0.5b-expo-DPO-ES-TRY
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
[<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/jz5qh3m8)
# qwen2.5-0.5b-expo-DPO-ES-TRY
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: 0.6866
- Logps: -91.4116
- Logits: -1.5339
- Objective: 0.6926
- Dpo Loss: 0.6926
- Regularize: 0.6926
- Ranking Simple: 0.5052
- Ranking Idealized: 0.5888
- Ranking Idealized Expo: 0.5093
- Dpo Wo Beta: -0.9551
## 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-07
- 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: 2
### Training results
| Training Loss | Epoch | Step | Dpo Loss | Dpo Wo Beta | Logits | Logps | Validation Loss | Objective | Ranking Idealized | Ranking Idealized Expo | Ranking Simple | Regularize |
|:-------------:|:------:|:----:|:--------:|:-----------:|:-------:|:---------:|:---------------:|:---------:|:-----------------:|:----------------------:|:--------------:|:----------:|
| 0.672 | 0.2041 | 36 | 0.6926 | -0.9551 | -1.5339 | -91.4116 | 0.6866 | 0.6926 | 0.5888 | 0.5093 | 0.5052 | 0.6926 |
| 0.6533 | 0.4081 | 72 | 0.6885 | -1.1473 | -1.6311 | -92.4758 | 0.6769 | 0.6885 | 0.5888 | 0.5093 | 0.5176 | 0.6885 |
| 0.604 | 0.6122 | 108 | 0.6853 | -1.3961 | -1.7691 | -94.0584 | 0.6773 | 0.6853 | 0.5888 | 0.5093 | 0.5186 | 0.6853 |
| 0.5911 | 0.8162 | 144 | 0.6886 | -1.5153 | -1.8165 | -95.7578 | 0.6775 | 0.6886 | 0.5888 | 0.5093 | 0.5186 | 0.6886 |
| 0.5482 | 1.0203 | 180 | 0.6859 | -98.1346 | -1.8457 | 0.6998 | 0.6998 | 0.6998 | 0.5238 | 0.5888 | 0.5093 | -1.8685 |
| 0.5171 | 1.2244 | 216 | 0.6891 | -99.3936 | -1.8859 | 0.7004 | 0.7004 | 0.7004 | 0.5248 | 0.5888 | 0.5093 | -2.0594 |
| 0.5093 | 1.4284 | 252 | 0.6999 | -102.0847 | -1.8968 | 0.7119 | 0.7119 | 0.7119 | 0.5238 | 0.5888 | 0.5093 | -2.3165 |
| 0.4986 | 1.6325 | 288 | 0.6981 | -102.1441 | -1.9005 | 0.7090 | 0.7090 | 0.7090 | 0.5279 | 0.5888 | 0.5093 | -2.2741 |
| 0.5055 | 1.8366 | 324 | 0.6965 | -101.5796 | -1.8981 | 0.7080 | 0.7080 | 0.7080 | 0.5279 | 0.5888 | 0.5093 | -2.2649 |
### Framework versions
- Transformers 4.42.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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