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---
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-EXPERIMENT-10-5e6
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/5jlf70he)
# qwen2.5-0.5b-expo-DPO-EXPERIMENT-10-5e6
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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 15.2566
- Logps: -80.3981
- Logits: -1.0046
- Objective: 15.1445
- Dpo Loss: 15.1445
- Regularize: 15.1445
- Ranking Simple: 0.5134
- Ranking Idealized: 0.5093
- Ranking Idealized Expo: 0.5093
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-----------------:|:----------------------:|
| 9.5723 | 0.2834 | 50 | 9.2586 | -89.6862 | -1.4979 | 9.6501 | 9.6501 | 9.6501 | 0.5134 | 0.5093 | 0.5093 |
| 9.8364 | 0.5668 | 100 | 15.5453 | -79.4201 | -1.3475 | 15.5409 | 15.5409 | 15.5409 | 0.5176 | 0.5093 | 0.5093 |
| 8.8451 | 0.8503 | 150 | 16.6626 | -82.1459 | -1.1122 | 16.5626 | 16.5626 | 16.5626 | 0.5145 | 0.5093 | 0.5093 |
| 3.8083 | 1.1337 | 200 | 16.0519 | -81.6751 | -1.0874 | 16.3240 | 16.3240 | 16.3240 | 0.5186 | 0.5093 | 0.5093 |
| 3.6019 | 1.4171 | 250 | 15.8144 | -81.5609 | -0.9933 | 15.7679 | 15.7679 | 15.7679 | 0.5176 | 0.5093 | 0.5093 |
| 2.1682 | 1.7005 | 300 | 15.3824 | -80.3329 | -1.0036 | 15.2004 | 15.2004 | 15.2004 | 0.5114 | 0.5093 | 0.5093 |
| 2.703 | 1.9839 | 350 | 15.2566 | -80.3981 | -1.0046 | 15.1445 | 15.1445 | 15.1445 | 0.5134 | 0.5093 | 0.5093 |
### Framework versions
- Transformers 4.42.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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