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---
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
- trl
- dpo
- alignment-handbook
- generated_from_trainer
model-index:
- name: zephyr-7b-dpo-full-gpt-reward-scale-05
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. -->
# zephyr-7b-dpo-full-gpt-reward-scale-05
This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co./alignment-handbook/zephyr-7b-sft-full) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5238
- Rewards/chosen: -1.1890
- Rewards/rejected: -2.1821
- Rewards/accuracies: 0.7241
- Rewards/margins: 0.9930
- Logps/rejected: -463.8542
- Logps/chosen: -402.9079
- Logits/rejected: 3.3069
- Logits/chosen: 1.9855
## 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: 8
- eval_batch_size: 8
- seed: 55
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6687 | 0.1147 | 50 | 0.6560 | -0.0264 | -0.1298 | 0.6724 | 0.1034 | -258.6246 | -286.6438 | -2.5075 | -2.6072 |
| 0.581 | 0.2294 | 100 | 0.5764 | -0.7311 | -1.3172 | 0.7155 | 0.5861 | -377.3666 | -357.1160 | 0.6340 | 0.0270 |
| 0.558 | 0.3440 | 150 | 0.5510 | -1.2031 | -1.9696 | 0.7241 | 0.7665 | -442.6071 | -404.3199 | 3.0036 | 2.0828 |
| 0.5346 | 0.4587 | 200 | 0.5381 | -1.1677 | -2.0355 | 0.7112 | 0.8679 | -449.2019 | -400.7711 | 2.7759 | 1.7577 |
| 0.5391 | 0.5734 | 250 | 0.5333 | -1.0858 | -1.9666 | 0.7198 | 0.8807 | -442.3041 | -392.5903 | 2.9561 | 1.8167 |
| 0.5479 | 0.6881 | 300 | 0.5265 | -1.0463 | -1.9706 | 0.7069 | 0.9243 | -442.7093 | -388.6379 | 3.2239 | 2.0026 |
| 0.5232 | 0.8028 | 350 | 0.5262 | -1.3359 | -2.3191 | 0.7241 | 0.9832 | -477.5577 | -417.5966 | 3.6066 | 2.3484 |
| 0.5267 | 0.9174 | 400 | 0.5238 | -1.1890 | -2.1821 | 0.7241 | 0.9930 | -463.8542 | -402.9079 | 3.3069 | 1.9855 |
### Framework versions
- Transformers 4.44.0.dev0
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
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