---
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-L2EXPO-noES2-0.1
  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/x320k7u5)
# qwen2.5-0.5b-expo-DPO-L2EXPO-noES2-0.1

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: 0.7416
- Logps: -92.3352
- Logits: -1.2949
- Objective: 0.7355
- Dpo Loss: 0.6749
- Ranking Simple: 0.5502

## 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: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Logps    | Logits  | Objective | Dpo Loss | Ranking Simple |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:--------:|:--------------:|
| 0.6826        | 0.1417 | 50   | 0.7254          | -92.3092 | -1.5368 | 0.7272    | 0.6828   | 0.5280         |
| 0.6518        | 0.2834 | 100  | 0.7251          | -99.4396 | -1.6149 | 0.7209    | 0.6727   | 0.5383         |
| 0.5964        | 0.4251 | 150  | 0.7330          | -90.2166 | -1.4409 | 0.7247    | 0.6714   | 0.5409         |
| 0.5794        | 0.5668 | 200  | 0.7543          | -90.8808 | -1.5459 | 0.7437    | 0.6858   | 0.5378         |
| 0.5802        | 0.7085 | 250  | 0.7559          | -86.8752 | -1.5326 | 0.7459    | 0.6874   | 0.5404         |
| 0.5473        | 0.8503 | 300  | 0.7457          | -92.3480 | -1.5370 | 0.7389    | 0.6780   | 0.5487         |
| 0.5104        | 0.9920 | 350  | 0.7516          | -88.1940 | -1.3364 | 0.7372    | 0.6766   | 0.5430         |
| 0.4425        | 1.1337 | 400  | 0.7568          | -88.7595 | -1.2226 | 0.7489    | 0.6866   | 0.5440         |
| 0.4544        | 1.2754 | 450  | 0.7455          | -90.0551 | -1.3089 | 0.7365    | 0.6750   | 0.5481         |
| 0.4624        | 1.4171 | 500  | 0.7470          | -89.6256 | -1.2445 | 0.7387    | 0.6782   | 0.5533         |
| 0.4391        | 1.5588 | 550  | 0.7385          | -91.9954 | -1.1983 | 0.7304    | 0.6695   | 0.5487         |
| 0.4285        | 1.7005 | 600  | 0.7408          | -91.4037 | -1.1181 | 0.7317    | 0.6726   | 0.5502         |
| 0.4553        | 1.8422 | 650  | 0.7426          | -90.4160 | -1.2725 | 0.7335    | 0.6740   | 0.5559         |
| 0.4307        | 1.9839 | 700  | 0.7404          | -91.7855 | -1.2351 | 0.7342    | 0.6735   | 0.5585         |
| 0.3755        | 2.1256 | 750  | 0.7430          | -93.2394 | -1.3013 | 0.7369    | 0.6762   | 0.5487         |
| 0.3794        | 2.2674 | 800  | 0.7400          | -93.3133 | -1.2647 | 0.7335    | 0.6726   | 0.5543         |
| 0.373         | 2.4091 | 850  | 0.7410          | -92.9388 | -1.2593 | 0.7354    | 0.6747   | 0.5523         |
| 0.388         | 2.5508 | 900  | 0.7418          | -92.8924 | -1.2939 | 0.7363    | 0.6757   | 0.5502         |
| 0.3866        | 2.6925 | 950  | 0.7418          | -92.3290 | -1.2937 | 0.7358    | 0.6752   | 0.5507         |
| 0.3828        | 2.8342 | 1000 | 0.7417          | -92.3260 | -1.2946 | 0.7356    | 0.6749   | 0.5502         |
| 0.3743        | 2.9759 | 1050 | 0.7416          | -92.3352 | -1.2949 | 0.7355    | 0.6749   | 0.5502         |


### Framework versions

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