---
library_name: transformers
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
- alignment-handbook
- trl
- dpo
- 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: 0.5004
- Rewards/chosen: -1.0684
- Rewards/rejected: -2.0671
- Rewards/accuracies: 0.7852
- Rewards/margins: 0.9987
- Logps/rejected: -469.3939
- Logps/chosen: -369.4198
- Logits/rejected: 0.7735
- Logits/chosen: -0.2945

## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- total_eval_batch_size: 64
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5644        | 0.2092 | 100  | 0.5693          | -0.4760        | -0.9833          | 0.75               | 0.5073          | -361.0131      | -310.1760    | -1.6463         | -1.8042       |
| 0.5482        | 0.4184 | 200  | 0.5285          | -0.5789        | -1.3324          | 0.7812             | 0.7535          | -395.9196      | -320.4612    | -1.1108         | -1.6512       |
| 0.4952        | 0.6276 | 300  | 0.5067          | -1.0198        | -1.9482          | 0.7734             | 0.9284          | -457.5016      | -364.5515    | 0.5574          | -0.3940       |
| 0.5037        | 0.8368 | 400  | 0.5006          | -1.0395        | -2.0108          | 0.7852             | 0.9713          | -463.7658      | -366.5239    | 0.6358          | -0.3905       |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0a0+f70bd71a48.nv24.06
- Datasets 2.18.0
- Tokenizers 0.20.0