---
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: zephyr-7b-dpo-full-gpt_consistent-reward-scale-1
  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-gpt_consistent-reward-scale-1

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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4815
- Rewards/chosen: -1.5849
- Rewards/rejected: -2.8045
- Rewards/accuracies: 0.7328
- Rewards/margins: 1.2196
- Logps/rejected: -526.9686
- Logps/chosen: -443.5758
- Logits/rejected: 3.4838
- Logits/chosen: 2.3333

## 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: 55
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6607        | 0.1147 | 50   | 0.6447          | -0.0044        | -0.1452          | 0.6897             | 0.1408          | -261.0398      | -285.5275    | -2.4923         | -2.5735       |
| 0.5616        | 0.2294 | 100  | 0.5464          | -0.8527        | -1.5772          | 0.6853             | 0.7245          | -404.2408      | -370.3625    | 0.2075          | -0.2410       |
| 0.5333        | 0.3440 | 150  | 0.5195          | -1.0024        | -1.8820          | 0.7112             | 0.8797          | -434.7274      | -385.3255    | 1.4808          | 0.5890        |
| 0.5219        | 0.4587 | 200  | 0.5010          | -1.0719        | -2.0541          | 0.7328             | 0.9822          | -451.9354      | -392.2838    | 2.4260          | 1.4256        |
| 0.5007        | 0.5734 | 250  | 0.4917          | -1.2321        | -2.3291          | 0.7241             | 1.0970          | -479.4298      | -408.2994    | 2.6738          | 1.4527        |
| 0.5109        | 0.6881 | 300  | 0.4878          | -1.3356        | -2.5048          | 0.7284             | 1.1691          | -496.9991      | -418.6534    | 2.8884          | 1.5762        |
| 0.5063        | 0.8028 | 350  | 0.4814          | -1.4870        | -2.6833          | 0.7371             | 1.1963          | -514.8549      | -433.7904    | 3.3469          | 2.1699        |
| 0.4936        | 0.9174 | 400  | 0.4815          | -1.5849        | -2.8045          | 0.7328             | 1.2196          | -526.9686      | -443.5758    | 3.4838          | 2.3333        |


### Framework versions

- Transformers 4.44.0.dev0
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1