---
license: apache-2.0
base_model: hZzy/qwen2.5-0.5b-sft-news-IFT
tags:
- trl
- expo
- generated_from_trainer
model-index:
- name: qwen2.5-0.5b-expo-DPO-ES-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/w0nbtpl2)
# qwen2.5-0.5b-expo-DPO-ES-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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7091
- Logps: -107.9610
- Logits: -1.9041
- Objective: 0.7134
- Dpo Loss: 0.7134
- Regularize: 0.7134
- Ranking Simple: 0.5616
- Ranking Idealized: 0.6030
- Ranking Idealized Expo: 0.5223
- Wo Beta: 8.1968

## 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: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Logps     | Logits  | Objective | Dpo Loss | Regularize | Ranking Simple | Ranking Idealized | Ranking Idealized Expo | Wo Beta |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-----------------:|:----------------------:|:-------:|
| 0.6785        | 0.1417 | 50   | 0.6814          | -90.8721  | -1.6022 | 0.6843    | 0.6843   | 0.6843     | 0.5259         | 0.6030            | 0.5223                 | 7.8749  |
| 0.618         | 0.2834 | 100  | 0.6733          | -98.8900  | -1.7799 | 0.6766    | 0.6766   | 0.6766     | 0.5399         | 0.6030            | 0.5223                 | 7.7840  |
| 0.5667        | 0.4251 | 150  | 0.6867          | -99.1217  | -1.8072 | 0.6829    | 0.6829   | 0.6829     | 0.5409         | 0.6030            | 0.5223                 | 7.8537  |
| 0.5214        | 0.5668 | 200  | 0.6902          | -99.5153  | -1.8895 | 0.6905    | 0.6905   | 0.6905     | 0.5445         | 0.6030            | 0.5223                 | 7.7013  |
| 0.4922        | 0.7085 | 250  | 0.6976          | -82.8384  | -1.9887 | 0.6914    | 0.6914   | 0.6914     | 0.5481         | 0.6030            | 0.5223                 | 7.8784  |
| 0.4535        | 0.8503 | 300  | 0.6923          | -90.9491  | -2.1209 | 0.6894    | 0.6894   | 0.6894     | 0.5564         | 0.6030            | 0.5223                 | 7.4232  |
| 0.4228        | 0.9920 | 350  | 0.7064          | -87.7231  | -1.9803 | 0.6968    | 0.6968   | 0.6968     | 0.5538         | 0.6030            | 0.5223                 | 8.0253  |
| 0.2845        | 1.1337 | 400  | 0.7305          | -101.3180 | -2.0805 | 0.7269    | 0.7269   | 0.7269     | 0.5430         | 0.6030            | 0.5223                 | 8.6164  |
| 0.2989        | 1.2754 | 450  | 0.7005          | -93.1955  | -1.8646 | 0.6974    | 0.6974   | 0.6974     | 0.5606         | 0.6030            | 0.5223                 | 8.2386  |
| 0.3065        | 1.4171 | 500  | 0.7179          | -97.0137  | -1.9983 | 0.7147    | 0.7147   | 0.7147     | 0.5549         | 0.6030            | 0.5223                 | 8.2760  |
| 0.2885        | 1.5588 | 550  | 0.7091          | -107.9610 | -1.9041 | 0.7134    | 0.7134   | 0.7134     | 0.5616         | 0.6030            | 0.5223                 | 8.1968  |


### Framework versions

- Transformers 4.42.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1