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---
license: apache-2.0
library_name: peft
tags:
- alignment-handbook
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
base_model: mistralai/Mistral-7B-v0.1
model-index:
- name: zephyr-7b-gpo-iter2
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-gpo-iter2
This model is a fine-tuned version of [DUAL-GPO/zephyr-7b-gpo-iter1](https://huggingface.co/DUAL-GPO/zephyr-7b-gpo-iter1) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0114
- Rewards/chosen: -0.0874
- Rewards/rejected: -0.0645
- Rewards/accuracies: 0.3940
- Rewards/margins: -0.0229
- Logps/rejected: -264.6114
- Logps/chosen: -288.2511
- Logits/rejected: -2.1907
- Logits/chosen: -2.3882
## 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: 1
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- 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 | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.0012 | 0.3 | 100 | 0.0016 | -0.0164 | -0.0160 | 0.5035 | -0.0005 | -259.7555 | -281.1500 | -2.1644 | -2.3583 |
| 0.0011 | 0.61 | 200 | 0.0018 | -0.0088 | -0.0077 | 0.4815 | -0.0011 | -258.9317 | -280.3858 | -2.1837 | -2.3781 |
| 0.0015 | 0.91 | 300 | 0.0019 | -0.0167 | -0.0149 | 0.4805 | -0.0017 | -259.6521 | -281.1740 | -2.1796 | -2.3740 |
| 0.0397 | 1.22 | 400 | 0.0074 | -0.0779 | -0.0627 | 0.4160 | -0.0151 | -264.4323 | -287.2935 | -2.1632 | -2.3568 |
| 0.0305 | 1.52 | 500 | 0.0117 | -0.0898 | -0.0668 | 0.3945 | -0.0230 | -264.8388 | -288.4842 | -2.1902 | -2.3875 |
| 0.0366 | 1.82 | 600 | 0.0115 | -0.0876 | -0.0647 | 0.4000 | -0.0230 | -264.6301 | -288.2723 | -2.1900 | -2.3873 |
### Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.14.6
- Tokenizers 0.15.2 |