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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-L2EXPO-EXPERIMENT-0.05-5e7
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/nswhwv8u)
# qwen2.5-0.5b-expo-L2EXPO-EXPERIMENT-0.05-5e7
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: 0.4176
- Logps: -99.8972
- Logits: -1.7324
- Objective: 0.4184
- Dpo Loss: 0.6853
- Regularize: 0.4184
- Ranking Simple: 0.5238
- 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-07
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------:|:---------:|:--------:|:----------:|:--------------:|:-----------------:|:----------------------:|
| 0.4122 | 0.2834 | 50 | 0.4102 | -90.5614 | -1.4615 | 0.4093 | 0.6915 | 0.4093 | 0.5124 | 0.6570 | 0.5114 |
| 0.374 | 0.5668 | 100 | 0.4073 | -92.0361 | -1.5521 | 0.4082 | 0.6883 | 0.4082 | 0.5145 | 0.6570 | 0.5114 |
| 0.3231 | 0.8503 | 150 | 0.4029 | -92.8073 | -1.6074 | 0.4087 | 0.6881 | 0.4087 | 0.5186 | 0.6570 | 0.5114 |
| 0.267 | 1.1337 | 200 | 0.4069 | -94.7992 | -1.6424 | 0.4110 | 0.6866 | 0.4110 | 0.5186 | 0.6570 | 0.5114 |
| 0.2432 | 1.4171 | 250 | 0.4108 | -96.1389 | -1.6721 | 0.4137 | 0.6877 | 0.4137 | 0.5196 | 0.6570 | 0.5114 |
| 0.2252 | 1.7005 | 300 | 0.4101 | -95.6244 | -1.6648 | 0.4138 | 0.6866 | 0.4138 | 0.5217 | 0.6570 | 0.5114 |
| 0.2082 | 1.9839 | 350 | 0.4102 | -97.5255 | -1.6989 | 0.4132 | 0.6863 | 0.4132 | 0.5196 | 0.6570 | 0.5114 |
| 0.1825 | 2.2674 | 400 | 0.4124 | -97.7996 | -1.6932 | 0.4144 | 0.6863 | 0.4144 | 0.5207 | 0.6570 | 0.5114 |
| 0.1504 | 2.5508 | 450 | 0.4149 | -99.2029 | -1.7113 | 0.4176 | 0.6864 | 0.4176 | 0.5217 | 0.6570 | 0.5114 |
| 0.1494 | 2.8342 | 500 | 0.4153 | -99.1755 | -1.7175 | 0.4182 | 0.6862 | 0.4182 | 0.5227 | 0.6570 | 0.5114 |
| 0.1407 | 3.1176 | 550 | 0.4161 | -99.2997 | -1.7183 | 0.4174 | 0.6856 | 0.4174 | 0.5217 | 0.6570 | 0.5114 |
| 0.1149 | 3.4010 | 600 | 0.4171 | -99.9246 | -1.7181 | 0.4181 | 0.6852 | 0.4181 | 0.5248 | 0.6570 | 0.5114 |
| 0.1108 | 3.6845 | 650 | 0.4178 | -99.9118 | -1.7315 | 0.4188 | 0.6853 | 0.4188 | 0.5248 | 0.6570 | 0.5114 |
| 0.1146 | 3.9679 | 700 | 0.4176 | -99.8982 | -1.7319 | 0.4187 | 0.6854 | 0.4187 | 0.5238 | 0.6570 | 0.5114 |
| 0.0986 | 4.2513 | 750 | 0.4175 | -99.8694 | -1.7322 | 0.4183 | 0.6853 | 0.4183 | 0.5238 | 0.6570 | 0.5114 |
| 0.1042 | 4.5347 | 800 | 0.4175 | -99.8600 | -1.7317 | 0.4183 | 0.6853 | 0.4183 | 0.5238 | 0.6570 | 0.5114 |
| 0.103 | 4.8181 | 850 | 0.4176 | -99.8972 | -1.7324 | 0.4184 | 0.6853 | 0.4184 | 0.5238 | 0.6570 | 0.5114 |
### Framework versions
- Transformers 4.42.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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