---
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
- alignment-handbook
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: zephyr-7b-dpo-full
  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

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 HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5046
- Rewards/chosen: -1.1826
- Rewards/rejected: -2.0581
- Rewards/accuracies: 0.7246
- Rewards/margins: 0.8756
- Logps/rejected: -470.5493
- Logps/chosen: -395.9858
- Logits/rejected: 0.0457
- Logits/chosen: -0.4473

## 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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- gradient_accumulation_steps: 10
- total_train_batch_size: 120
- total_eval_batch_size: 12
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5764        | 0.2   | 100  | 0.5829          | -0.3592        | -0.7613          | 0.6931             | 0.4020          | -340.8605      | -313.6503    | -2.4360         | -2.4791       |
| 0.5169        | 0.39  | 200  | 0.5312          | -0.8847        | -1.6204          | 0.7066             | 0.7356          | -426.7720      | -366.2012    | -0.8443         | -1.2010       |
| 0.5133        | 0.59  | 300  | 0.5159          | -1.1886        | -1.9604          | 0.7246             | 0.7718          | -460.7765      | -396.5906    | 0.0460          | -0.3853       |
| 0.4968        | 0.79  | 400  | 0.5058          | -1.2445        | -2.1063          | 0.7141             | 0.8618          | -475.3639      | -402.1766    | 0.2014          | -0.2552       |
| 0.4833        | 0.98  | 500  | 0.5045          | -1.1821        | -2.0581          | 0.7260             | 0.8760          | -470.5448      | -395.9374    | 0.0436          | -0.4496       |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2