---
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-iter0
  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-iter0

This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-qlora](https://huggingface.co/alignment-handbook/zephyr-7b-sft-qlora) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0258
- Rewards/chosen: -0.0580
- Rewards/rejected: -0.0061
- Rewards/accuracies: 0.3380
- Rewards/margins: -0.0519
- Logps/rejected: -249.4468
- Logps/chosen: -274.3866
- Logits/rejected: -2.2108
- Logits/chosen: -2.4070

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.0008        | 0.2   | 100  | 0.0019          | -0.0111        | -0.0138          | 0.5300             | 0.0027          | -250.2170      | -269.6990    | -2.2026         | -2.4007       |
| 0.0006        | 0.4   | 200  | 0.0029          | -0.0237        | -0.0230          | 0.4910             | -0.0007         | -251.1392      | -270.9541    | -2.2051         | -2.4034       |
| 0.001         | 0.6   | 300  | 0.0019          | -0.0120        | -0.0142          | 0.5310             | 0.0022          | -250.2602      | -269.7912    | -2.2008         | -2.3984       |
| 0.0011        | 0.8   | 400  | 0.0023          | -0.0201        | -0.0211          | 0.5010             | 0.0011          | -250.9541      | -270.5950    | -2.1993         | -2.3968       |
| 0.0008        | 1.0   | 500  | 0.0021          | -0.0170        | -0.0189          | 0.5065             | 0.0019          | -250.7260      | -270.2850    | -2.1982         | -2.3960       |
| 0.044         | 1.2   | 600  | 0.0091          | -0.0053        | 0.0198           | 0.3600             | -0.0252         | -246.8548      | -269.1194    | -2.1940         | -2.3899       |
| 0.0682        | 1.4   | 700  | 0.0191          | -0.0345        | 0.0086           | 0.3450             | -0.0431         | -247.9818      | -272.0423    | -2.2035         | -2.3992       |
| 0.0505        | 1.6   | 800  | 0.0237          | -0.0497        | -0.0001          | 0.3405             | -0.0496         | -248.8542      | -273.5587    | -2.2094         | -2.4056       |
| 0.0243        | 1.8   | 900  | 0.0259          | -0.0581        | -0.0062          | 0.3340             | -0.0519         | -249.4570      | -274.3967    | -2.2117         | -2.4081       |
| 0.0697        | 2.0   | 1000 | 0.0258          | -0.0580        | -0.0061          | 0.3380             | -0.0519         | -249.4468      | -274.3866    | -2.2108         | -2.4070       |


### Framework versions

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