---
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-noES3-0.1
  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/ffrdf5px)
# qwen2.5-0.5b-expo-DPO-noES3-0.1

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: 0.7566
- Logps: -117.9870
- Logits: -1.9778
- Objective: 0.7537
- Dpo Loss: 0.7537
- Regularize: 0.7537
- Ranking Simple: 0.5595
- Wo Beta: 9.1042

## 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 | Regularize | Ranking Simple | Wo Beta |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-------:|
| 0.6316        | 0.1417 | 50   | 0.6807          | -90.3282  | -1.5879 | 0.6825    | 0.6825   | 0.6825     | 0.5342         | 7.8619  |
| 0.5922        | 0.2834 | 100  | 0.6793          | -95.8152  | -1.7964 | 0.6819    | 0.6819   | 0.6819     | 0.5487         | 7.7077  |
| 0.5002        | 0.4251 | 150  | 0.6815          | -96.2024  | -1.5951 | 0.6749    | 0.6749   | 0.6749     | 0.5497         | 7.4380  |
| 0.4735        | 0.5668 | 200  | 0.6951          | -98.9176  | -1.7564 | 0.6911    | 0.6911   | 0.6911     | 0.5569         | 7.5241  |
| 0.4626        | 0.7085 | 250  | 0.6976          | -93.4775  | -1.7986 | 0.6945    | 0.6945   | 0.6945     | 0.5580         | 7.9027  |
| 0.4214        | 0.8503 | 300  | 0.6931          | -104.4337 | -2.0138 | 0.6865    | 0.6865   | 0.6865     | 0.5616         | 7.5814  |
| 0.3652        | 0.9920 | 350  | 0.7074          | -102.8306 | -1.9094 | 0.6984    | 0.6984   | 0.6984     | 0.5559         | 7.8344  |
| 0.2206        | 1.1337 | 400  | 0.7347          | -113.6048 | -2.0909 | 0.7296    | 0.7296   | 0.7296     | 0.5502         | 8.6751  |
| 0.2202        | 1.2754 | 450  | 0.7463          | -115.7782 | -1.9911 | 0.7433    | 0.7433   | 0.7433     | 0.5512         | 8.9123  |
| 0.2366        | 1.4171 | 500  | 0.7444          | -114.7710 | -2.0464 | 0.7387    | 0.7387   | 0.7387     | 0.5518         | 8.8630  |
| 0.1989        | 1.5588 | 550  | 0.7553          | -118.7775 | -2.0168 | 0.7519    | 0.7519   | 0.7519     | 0.5595         | 8.9846  |
| 0.1952        | 1.7005 | 600  | 0.7544          | -117.4880 | -1.9707 | 0.7513    | 0.7513   | 0.7513     | 0.5595         | 9.0297  |
| 0.2252        | 1.8422 | 650  | 0.7560          | -117.8008 | -1.9748 | 0.7529    | 0.7529   | 0.7529     | 0.5585         | 9.0926  |
| 0.199         | 1.9839 | 700  | 0.7566          | -117.9869 | -1.9778 | 0.7537    | 0.7537   | 0.7537     | 0.5595         | 9.1042  |


### Framework versions

- Transformers 4.42.0
- Pytorch 2.3.0+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1