---
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-iter1
  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-iter1

This model is a fine-tuned version of [DUAL-GPO/zephyr-7b-gpo-iter0](https://huggingface.co/DUAL-GPO/zephyr-7b-gpo-iter0) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0069
- Rewards/chosen: 0.0025
- Rewards/rejected: 0.0081
- Rewards/accuracies: 0.4595
- Rewards/margins: -0.0056
- Logps/rejected: -272.5866
- Logps/chosen: -298.8498
- Logits/rejected: -2.1749
- Logits/chosen: -2.3692

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.0006        | 0.2   | 100  | 0.0031          | -0.0541        | -0.0467          | 0.4245             | -0.0074         | -278.0669      | -304.5065    | -2.1506         | -2.3436       |
| 0.0025        | 0.4   | 200  | 0.0033          | -0.0115        | -0.0107          | 0.4910             | -0.0008         | -274.4619      | -300.2420    | -2.1684         | -2.3612       |
| 0.0009        | 0.6   | 300  | 0.0030          | -0.0220        | -0.0216          | 0.4935             | -0.0004         | -275.5567      | -301.2960    | -2.1427         | -2.3360       |
| 0.0013        | 0.8   | 400  | 0.0034          | -0.0156        | -0.0142          | 0.4935             | -0.0014         | -274.8156      | -300.6561    | -2.1462         | -2.3405       |
| 0.0011        | 1.0   | 500  | 0.0037          | -0.0565        | -0.0502          | 0.4520             | -0.0063         | -278.4165      | -304.7457    | -2.1454         | -2.3392       |
| 0.0116        | 1.2   | 600  | 0.0049          | -0.0283        | -0.0229          | 0.4435             | -0.0054         | -275.6791      | -301.9266    | -2.1527         | -2.3449       |
| 0.015         | 1.4   | 700  | 0.0065          | -0.0261        | -0.0182          | 0.4450             | -0.0078         | -275.2170      | -301.7041    | -2.1650         | -2.3586       |
| 0.0009        | 1.6   | 800  | 0.0069          | 0.0079         | 0.0124           | 0.4720             | -0.0044         | -272.1540      | -298.3011    | -2.1746         | -2.3689       |
| 0.0109        | 1.8   | 900  | 0.0069          | 0.0024         | 0.0080           | 0.4570             | -0.0057         | -272.5880      | -298.8583    | -2.1739         | -2.3682       |
| 0.0015        | 2.0   | 1000 | 0.0069          | 0.0025         | 0.0081           | 0.4595             | -0.0056         | -272.5866      | -298.8498    | -2.1749         | -2.3692       |


### Framework versions

- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.14.6
- Tokenizers 0.15.2