---
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
- trl
- dpo
- alignment-handbook
- generated_from_trainer
model-index:
- name: zephyr-7b-dpo-full-prometheus_consistent-reward-scale-01
  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-prometheus_consistent-reward-scale-01

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: 0.5426
- Rewards/chosen: -1.6823
- Rewards/rejected: -3.0793
- Rewards/accuracies: 0.7543
- Rewards/margins: 1.3969
- Logps/rejected: -527.0015
- Logps/chosen: -443.8361
- Logits/rejected: 3.9256
- Logits/chosen: 2.3196

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6745        | 0.1143 | 50   | 0.6652          | -0.0243        | -0.1726          | 0.6853             | 0.1483          | -236.3333      | -278.0297    | -2.4359         | -2.5373       |
| 0.6243        | 0.2286 | 100  | 0.6148          | -0.4908        | -1.0266          | 0.7026             | 0.5358          | -321.7332      | -324.6850    | -2.3884         | -2.4967       |
| 0.5613        | 0.3429 | 150  | 0.5828          | -1.5541        | -2.6485          | 0.7241             | 1.0943          | -483.9227      | -431.0166    | 1.8439          | 0.7832        |
| 0.5618        | 0.4571 | 200  | 0.5594          | -1.3157        | -2.5436          | 0.7457             | 1.2279          | -473.4366      | -407.1749    | 2.6334          | 1.3535        |
| 0.558         | 0.5714 | 250  | 0.5526          | -1.3313        | -2.5932          | 0.7629             | 1.2619          | -478.3948      | -408.7301    | 3.1078          | 1.5316        |
| 0.5399        | 0.6857 | 300  | 0.5465          | -1.7354        | -3.0859          | 0.75               | 1.3504          | -527.6615      | -449.1465    | 3.8100          | 2.3192        |
| 0.5536        | 0.8    | 350  | 0.5458          | -1.8434        | -3.1830          | 0.7672             | 1.3396          | -537.3768      | -459.9458    | 4.1008          | 2.5496        |
| 0.5612        | 0.9143 | 400  | 0.5426          | -1.6823        | -3.0793          | 0.7543             | 1.3969          | -527.0015      | -443.8361    | 3.9256          | 2.3196        |


### Framework versions

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