---
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