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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-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
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