---
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: []
---

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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