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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_weighted
model-index:
- name: qwen2.5-0.5b-expo-DPO-noES3-0.1
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/ffrdf5px)
# qwen2.5-0.5b-expo-DPO-noES3-0.1
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 the hZzy/train_pairwise_weighted dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7566
- Logps: -117.9870
- Logits: -1.9778
- Objective: 0.7537
- Dpo Loss: 0.7537
- Regularize: 0.7537
- Ranking Simple: 0.5595
- Wo Beta: 9.1042
## 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: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss | Logps | Logits | Objective | Dpo Loss | Regularize | Ranking Simple | Wo Beta |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-------:|
| 0.6316 | 0.1417 | 50 | 0.6807 | -90.3282 | -1.5879 | 0.6825 | 0.6825 | 0.6825 | 0.5342 | 7.8619 |
| 0.5922 | 0.2834 | 100 | 0.6793 | -95.8152 | -1.7964 | 0.6819 | 0.6819 | 0.6819 | 0.5487 | 7.7077 |
| 0.5002 | 0.4251 | 150 | 0.6815 | -96.2024 | -1.5951 | 0.6749 | 0.6749 | 0.6749 | 0.5497 | 7.4380 |
| 0.4735 | 0.5668 | 200 | 0.6951 | -98.9176 | -1.7564 | 0.6911 | 0.6911 | 0.6911 | 0.5569 | 7.5241 |
| 0.4626 | 0.7085 | 250 | 0.6976 | -93.4775 | -1.7986 | 0.6945 | 0.6945 | 0.6945 | 0.5580 | 7.9027 |
| 0.4214 | 0.8503 | 300 | 0.6931 | -104.4337 | -2.0138 | 0.6865 | 0.6865 | 0.6865 | 0.5616 | 7.5814 |
| 0.3652 | 0.9920 | 350 | 0.7074 | -102.8306 | -1.9094 | 0.6984 | 0.6984 | 0.6984 | 0.5559 | 7.8344 |
| 0.2206 | 1.1337 | 400 | 0.7347 | -113.6048 | -2.0909 | 0.7296 | 0.7296 | 0.7296 | 0.5502 | 8.6751 |
| 0.2202 | 1.2754 | 450 | 0.7463 | -115.7782 | -1.9911 | 0.7433 | 0.7433 | 0.7433 | 0.5512 | 8.9123 |
| 0.2366 | 1.4171 | 500 | 0.7444 | -114.7710 | -2.0464 | 0.7387 | 0.7387 | 0.7387 | 0.5518 | 8.8630 |
| 0.1989 | 1.5588 | 550 | 0.7553 | -118.7775 | -2.0168 | 0.7519 | 0.7519 | 0.7519 | 0.5595 | 8.9846 |
| 0.1952 | 1.7005 | 600 | 0.7544 | -117.4880 | -1.9707 | 0.7513 | 0.7513 | 0.7513 | 0.5595 | 9.0297 |
| 0.2252 | 1.8422 | 650 | 0.7560 | -117.8008 | -1.9748 | 0.7529 | 0.7529 | 0.7529 | 0.5585 | 9.0926 |
| 0.199 | 1.9839 | 700 | 0.7566 | -117.9869 | -1.9778 | 0.7537 | 0.7537 | 0.7537 | 0.5595 | 9.1042 |
### Framework versions
- Transformers 4.42.0
- Pytorch 2.3.0+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1
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