---
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
model-index:
- name: qwen2.5-0.5b-expo-L2EXPO-EXPERIMENT-0.1-1e6
  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/ytwqoneq)
# qwen2.5-0.5b-expo-L2EXPO-EXPERIMENT-0.1-1e6

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 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4062
- Logps: -90.0446
- Logits: -1.4303
- Objective: 0.4077
- Dpo Loss: 0.6829
- Regularize: 0.4077
- Ranking Simple: 0.5248
- Ranking Idealized: 0.5888
- Ranking Idealized Expo: 0.5103

## 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: 1e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 6
- gradient_accumulation_steps: 12
- total_train_batch_size: 288
- total_eval_batch_size: 24
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-----------------:|:----------------------:|
| 0.3854        | 0.2834 | 50   | 0.4056          | -91.4065 | -1.4801 | 0.4076    | 0.6886   | 0.4076     | 0.5124         | 0.5888            | 0.5103                 |
| 0.3126        | 0.5668 | 100  | 0.4022          | -91.3166 | -1.4526 | 0.4009    | 0.6817   | 0.4009     | 0.5207         | 0.5888            | 0.5103                 |
| 0.2481        | 0.8503 | 150  | 0.4118          | -93.3285 | -1.4781 | 0.4156    | 0.6853   | 0.4156     | 0.5186         | 0.5888            | 0.5103                 |
| 0.1986        | 1.1337 | 200  | 0.4053          | -90.6332 | -1.4691 | 0.4089    | 0.6828   | 0.4089     | 0.5207         | 0.5888            | 0.5103                 |
| 0.1805        | 1.4171 | 250  | 0.4086          | -90.2497 | -1.4648 | 0.4084    | 0.6831   | 0.4084     | 0.5248         | 0.5888            | 0.5103                 |
| 0.1668        | 1.7005 | 300  | 0.4080          | -89.8657 | -1.4761 | 0.4114    | 0.6842   | 0.4114     | 0.5207         | 0.5888            | 0.5103                 |
| 0.1476        | 1.9839 | 350  | 0.4086          | -89.6008 | -1.4348 | 0.4084    | 0.6835   | 0.4084     | 0.5217         | 0.5888            | 0.5103                 |
| 0.1232        | 2.2674 | 400  | 0.4064          | -89.9367 | -1.4142 | 0.4060    | 0.6825   | 0.4060     | 0.5238         | 0.5888            | 0.5103                 |
| 0.1085        | 2.5508 | 450  | 0.4057          | -90.6112 | -1.4381 | 0.4068    | 0.6829   | 0.4068     | 0.5238         | 0.5888            | 0.5103                 |
| 0.099         | 2.8342 | 500  | 0.4075          | -89.7867 | -1.4538 | 0.4090    | 0.6837   | 0.4090     | 0.5248         | 0.5888            | 0.5103                 |
| 0.0841        | 3.1176 | 550  | 0.4074          | -89.1923 | -1.4288 | 0.4091    | 0.6836   | 0.4091     | 0.5269         | 0.5888            | 0.5103                 |
| 0.0673        | 3.4010 | 600  | 0.4056          | -89.8307 | -1.4326 | 0.4069    | 0.6824   | 0.4069     | 0.5238         | 0.5888            | 0.5103                 |
| 0.0589        | 3.6845 | 650  | 0.4060          | -89.4758 | -1.4302 | 0.4077    | 0.6829   | 0.4077     | 0.5248         | 0.5888            | 0.5103                 |
| 0.0551        | 3.9679 | 700  | 0.4065          | -90.0660 | -1.4301 | 0.4080    | 0.6831   | 0.4080     | 0.5238         | 0.5888            | 0.5103                 |
| 0.042         | 4.2513 | 750  | 0.4064          | -90.0447 | -1.4307 | 0.4078    | 0.6830   | 0.4078     | 0.5248         | 0.5888            | 0.5103                 |
| 0.0411        | 4.5347 | 800  | 0.4062          | -90.1140 | -1.4310 | 0.4078    | 0.6830   | 0.4078     | 0.5238         | 0.5888            | 0.5103                 |
| 0.0355        | 4.8181 | 850  | 0.4062          | -90.0432 | -1.4302 | 0.4077    | 0.6829   | 0.4077     | 0.5248         | 0.5888            | 0.5103                 |


### Framework versions

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