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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_weighted
model-index:
- name: qwen2.5-0.5b-expo-DPO-noES5-1
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/ka5w2jn7)
# qwen2.5-0.5b-expo-DPO-noES5-1
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_weighted dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9399
- Logps: -81.1684
- Logits: -0.8509
- Objective: 1.8787
- Dpo Loss: 1.8787
- Ranking Simple: 0.5347
## 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: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Logps | Logits | Objective | Dpo Loss | Ranking Simple |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:--------:|:--------------:|
| 1.1219 | 0.1417 | 50 | 1.1407 | -91.1504 | -1.3894 | 1.1280 | 1.1280 | 0.5274 |
| 1.3821 | 0.2834 | 100 | 1.5304 | -81.2234 | -1.3774 | 1.4947 | 1.4947 | 0.5290 |
| 1.4062 | 0.4251 | 150 | 1.8818 | -79.7787 | -1.1641 | 1.8192 | 1.8192 | 0.5430 |
| 1.2275 | 0.5668 | 200 | 2.0358 | -77.9854 | -1.1289 | 1.9717 | 1.9717 | 0.5347 |
| 1.1914 | 0.7085 | 250 | 2.0084 | -78.3385 | -1.0883 | 1.9461 | 1.9461 | 0.5347 |
| 1.0378 | 0.8503 | 300 | 2.0918 | -83.4707 | -0.9324 | 2.0357 | 2.0357 | 0.5352 |
| 0.8334 | 0.9920 | 350 | 2.1143 | -81.1740 | -0.8755 | 1.9975 | 1.9975 | 0.5388 |
| 0.4251 | 1.1337 | 400 | 2.0641 | -81.1689 | -0.8003 | 2.0241 | 2.0241 | 0.5435 |
| 0.3886 | 1.2754 | 450 | 2.0085 | -79.8813 | -0.8999 | 1.9598 | 1.9598 | 0.5388 |
| 0.4352 | 1.4171 | 500 | 2.0449 | -80.7357 | -0.8634 | 1.9819 | 1.9819 | 0.5367 |
| 0.3103 | 1.5588 | 550 | 1.9784 | -80.8827 | -0.8672 | 1.9073 | 1.9073 | 0.5373 |
| 0.2489 | 1.7005 | 600 | 1.9488 | -81.0833 | -0.8421 | 1.8851 | 1.8851 | 0.5367 |
| 0.3631 | 1.8422 | 650 | 1.9417 | -81.1721 | -0.8529 | 1.8805 | 1.8805 | 0.5347 |
| 0.3009 | 1.9839 | 700 | 1.9399 | -81.1684 | -0.8509 | 1.8787 | 1.8787 | 0.5347 |
### Framework versions
- Transformers 4.42.0
- Pytorch 2.3.0+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1
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