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---
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-DPO-EXPERIMENT-0.1-5e6
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/aifgjuia)
# qwen2.5-0.5b-expo-DPO-EXPERIMENT-0.1-5e6
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: 0.7556
- Logps: -120.0429
- Logits: -1.9737
- Objective: 0.7840
- Dpo Loss: 0.7840
- Regularize: 0.7840
- Ranking Simple: 0.5403
- 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: 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: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Logps | Logits | Objective | Dpo Loss | Regularize | Ranking Simple | Ranking Idealized | Ranking Idealized Expo |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-----------------:|:----------------------:|
| 0.5807 | 0.2834 | 50 | 0.6822 | -101.8611 | -1.8709 | 0.7088 | 0.7088 | 0.7088 | 0.5196 | 0.5888 | 0.5103 |
| 0.4908 | 0.5668 | 100 | 0.6802 | -105.0768 | -1.8507 | 0.6854 | 0.6854 | 0.6854 | 0.5300 | 0.5888 | 0.5103 |
| 0.4191 | 0.8503 | 150 | 0.6960 | -108.5704 | -2.1205 | 0.7127 | 0.7127 | 0.7127 | 0.5403 | 0.5888 | 0.5103 |
| 0.2287 | 1.1337 | 200 | 0.7276 | -115.4432 | -2.0764 | 0.7403 | 0.7403 | 0.7403 | 0.5362 | 0.5888 | 0.5103 |
| 0.2329 | 1.4171 | 250 | 0.7454 | -118.2405 | -2.0640 | 0.7706 | 0.7706 | 0.7706 | 0.5351 | 0.5888 | 0.5103 |
| 0.2036 | 1.7005 | 300 | 0.7574 | -120.7682 | -1.9746 | 0.7851 | 0.7851 | 0.7851 | 0.5434 | 0.5888 | 0.5103 |
| 0.2102 | 1.9839 | 350 | 0.7556 | -120.0429 | -1.9737 | 0.7840 | 0.7840 | 0.7840 | 0.5403 | 0.5888 | 0.5103 |
### Framework versions
- Transformers 4.42.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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