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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-L2EXPO-EXPERIMENT-50-5e6
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/a6pnerr5)
# qwen2.5-0.5b-expo-L2EXPO-EXPERIMENT-50-5e6
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: 223.1421
- Logps: -81.8519
- Logits: -0.6524
- Objective: 224.3911
- Dpo Loss: 114.2648
- Regularize: 224.3911
- Ranking Simple: 0.5083
- Ranking Idealized: 0.5093
- Ranking Idealized Expo: 0.5093
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-----------------:|:----------------------:|
| 72.7249 | 0.2834 | 50 | 49.7663 | -92.8163 | -1.3016 | 48.7266 | 25.8845 | 48.7266 | 0.5083 | 0.5093 | 0.5093 |
| 152.2211 | 0.5668 | 100 | 146.6511 | -80.6726 | -1.2458 | 149.0543 | 74.5413 | 149.0543 | 0.5124 | 0.5093 | 0.5093 |
| 149.0411 | 0.8503 | 150 | 179.0229 | -81.4258 | -0.9511 | 179.4755 | 89.5257 | 179.4755 | 0.5124 | 0.5093 | 0.5093 |
| 135.6758 | 1.1337 | 200 | 190.7774 | -83.1371 | -0.8760 | 195.4946 | 98.7297 | 195.4946 | 0.5083 | 0.5093 | 0.5093 |
| 122.9397 | 1.4171 | 250 | 204.8156 | -81.1880 | -0.8410 | 206.5414 | 104.7900 | 206.5414 | 0.4990 | 0.5093 | 0.5093 |
| 109.8686 | 1.7005 | 300 | 216.4334 | -82.2344 | -0.6658 | 216.9471 | 109.1882 | 216.9471 | 0.5083 | 0.5093 | 0.5093 |
| 97.6956 | 1.9839 | 350 | 218.2887 | -81.0804 | -0.6323 | 217.4291 | 109.8084 | 217.4291 | 0.5072 | 0.5093 | 0.5093 |
| 86.0309 | 2.2674 | 400 | 221.7113 | -83.6082 | -0.5904 | 225.3389 | 115.8749 | 225.3389 | 0.5052 | 0.5093 | 0.5093 |
| 78.4362 | 2.5508 | 450 | 221.3732 | -82.0743 | -0.6173 | 224.4839 | 116.2117 | 224.4839 | 0.5114 | 0.5093 | 0.5093 |
| 65.179 | 2.8342 | 500 | 223.8012 | -82.3425 | -0.6892 | 227.1755 | 114.9871 | 227.1755 | 0.5083 | 0.5093 | 0.5093 |
| 52.3116 | 3.1176 | 550 | 223.6770 | -81.8433 | -0.6290 | 226.7591 | 114.9252 | 226.7591 | 0.5103 | 0.5093 | 0.5093 |
| 45.9426 | 3.4010 | 600 | 222.4720 | -81.3168 | -0.6183 | 223.1873 | 113.6331 | 223.1873 | 0.5072 | 0.5093 | 0.5093 |
| 37.3789 | 3.6845 | 650 | 223.4119 | -81.7013 | -0.6355 | 225.2157 | 114.6103 | 225.2157 | 0.5072 | 0.5093 | 0.5093 |
| 32.7043 | 3.9679 | 700 | 223.5499 | -81.8343 | -0.6585 | 224.4542 | 114.2602 | 224.4542 | 0.5062 | 0.5093 | 0.5093 |
| 22.8627 | 4.2513 | 750 | 223.7742 | -81.7547 | -0.6564 | 224.6748 | 114.4499 | 224.6748 | 0.5072 | 0.5093 | 0.5093 |
| 19.3618 | 4.5347 | 800 | 223.2886 | -81.8898 | -0.6540 | 224.4371 | 114.3485 | 224.4371 | 0.5083 | 0.5093 | 0.5093 |
| 18.3796 | 4.8181 | 850 | 223.1902 | -81.8524 | -0.6522 | 224.4282 | 114.2867 | 224.4282 | 0.5083 | 0.5093 | 0.5093 |
### Framework versions
- Transformers 4.42.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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