---
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-0.05-5e6
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

[<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/yzayr01r)
# qwen2.5-0.5b-expo-L2EXPO-EXPERIMENT-0.05-5e6

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: 0.4402
- Logps: -77.2011
- Logits: -0.8985
- Objective: 0.4385
- Dpo Loss: 0.6860
- Regularize: 0.4385
- Ranking Simple: 0.5320
- Ranking Idealized: 0.6570
- Ranking Idealized Expo: 0.5114

## 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: 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-----------------:|:----------------------:|
| 0.3566        | 0.2834 | 50   | 0.4133          | -96.4831 | -1.6203 | 0.4237    | 0.6898   | 0.4237     | 0.5165         | 0.6570            | 0.5114                 |
| 0.3027        | 0.5668 | 100  | 0.4142          | -88.4100 | -1.3063 | 0.4151    | 0.6862   | 0.4151     | 0.5217         | 0.6570            | 0.5114                 |
| 0.2706        | 0.8503 | 150  | 0.4262          | -87.3674 | -1.1981 | 0.4277    | 0.6857   | 0.4277     | 0.5279         | 0.6570            | 0.5114                 |
| 0.2256        | 1.1337 | 200  | 0.4347          | -81.8119 | -1.2023 | 0.4344    | 0.6862   | 0.4344     | 0.5248         | 0.6570            | 0.5114                 |
| 0.2005        | 1.4171 | 250  | 0.4292          | -81.8212 | -1.0616 | 0.4289    | 0.6815   | 0.4289     | 0.5227         | 0.6570            | 0.5114                 |
| 0.187         | 1.7005 | 300  | 0.4369          | -80.0077 | -1.0398 | 0.4362    | 0.6845   | 0.4362     | 0.5258         | 0.6570            | 0.5114                 |
| 0.1664        | 1.9839 | 350  | 0.4382          | -79.6308 | -0.9982 | 0.4359    | 0.6842   | 0.4359     | 0.5289         | 0.6570            | 0.5114                 |
| 0.1368        | 2.2674 | 400  | 0.4408          | -80.2038 | -1.0155 | 0.4378    | 0.6859   | 0.4378     | 0.5320         | 0.6570            | 0.5114                 |
| 0.122         | 2.5508 | 450  | 0.4415          | -78.4288 | -0.8946 | 0.4404    | 0.6863   | 0.4404     | 0.5258         | 0.6570            | 0.5114                 |
| 0.1063        | 2.8342 | 500  | 0.4411          | -78.1278 | -0.8683 | 0.4384    | 0.6861   | 0.4384     | 0.5300         | 0.6570            | 0.5114                 |
| 0.0878        | 3.1176 | 550  | 0.4406          | -77.6391 | -0.8292 | 0.4378    | 0.6848   | 0.4378     | 0.5331         | 0.6570            | 0.5114                 |
| 0.0719        | 3.4010 | 600  | 0.4396          | -77.4923 | -0.8875 | 0.4373    | 0.6851   | 0.4373     | 0.5310         | 0.6570            | 0.5114                 |
| 0.0618        | 3.6845 | 650  | 0.4395          | -77.1838 | -0.9103 | 0.4386    | 0.6855   | 0.4386     | 0.5269         | 0.6570            | 0.5114                 |
| 0.0551        | 3.9679 | 700  | 0.4402          | -77.7209 | -0.9137 | 0.4388    | 0.6859   | 0.4388     | 0.5289         | 0.6570            | 0.5114                 |
| 0.0388        | 4.2513 | 750  | 0.4404          | -77.0700 | -0.8976 | 0.4386    | 0.6859   | 0.4386     | 0.5310         | 0.6570            | 0.5114                 |
| 0.0382        | 4.5347 | 800  | 0.4402          | -77.2473 | -0.8972 | 0.4384    | 0.6859   | 0.4384     | 0.5320         | 0.6570            | 0.5114                 |
| 0.032         | 4.8181 | 850  | 0.4402          | -77.2053 | -0.8983 | 0.4385    | 0.6860   | 0.4385     | 0.5320         | 0.6570            | 0.5114                 |


### Framework versions

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