---
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: 0.5042
- Rewards/chosen: -1.0500
- Rewards/rejected: -2.0480
- Rewards/accuracies: 0.7539
- Rewards/margins: 0.9980
- Logps/rejected: -468.1450
- Logps/chosen: -368.4135
- Logits/rejected: 2.3821
- Logits/chosen: 1.6141

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5723        | 0.21  | 100  | 0.5851          | -0.4097        | -0.8752          | 0.7031             | 0.4655          | -350.8695      | -304.3812    | -2.3494         | -2.4070       |
| 0.5084        | 0.42  | 200  | 0.5251          | -0.9116        | -1.7472          | 0.7422             | 0.8355          | -438.0663      | -354.5790    | 1.3918          | 0.9248        |
| 0.5059        | 0.63  | 300  | 0.5130          | -0.8646        | -1.7542          | 0.75               | 0.8896          | -438.7735      | -349.8758    | 2.0331          | 1.2558        |
| 0.4853        | 0.84  | 400  | 0.5050          | -1.0929        | -2.1085          | 0.7539             | 1.0156          | -474.1963      | -372.7067    | 2.5922          | 1.8194        |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.0