---
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-prometheus-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-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: 0.5012
- Rewards/chosen: -1.7553
- Rewards/rejected: -2.9981
- Rewards/accuracies: 0.7198
- Rewards/margins: 1.2428
- Logps/rejected: -548.0841
- Logps/chosen: -435.4877
- Logits/rejected: 3.0596
- Logits/chosen: 1.9658

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6661        | 0.1143 | 50   | 0.6541          | -0.0354        | -0.1594          | 0.6552             | 0.1240          | -264.2141      | -263.4992    | -2.5732         | -2.6193       |
| 0.561         | 0.2286 | 100  | 0.5663          | -1.0515        | -1.8367          | 0.7069             | 0.7852          | -431.9447      | -365.1131    | -0.0076         | -0.4111       |
| 0.5324        | 0.3429 | 150  | 0.5437          | -1.4518        | -2.4385          | 0.6853             | 0.9868          | -492.1300      | -405.1368    | 2.0029          | 1.3258        |
| 0.5261        | 0.4571 | 200  | 0.5247          | -1.5625        | -2.5913          | 0.6853             | 1.0288          | -507.4055      | -416.2077    | 2.7389          | 1.7313        |
| 0.5274        | 0.5714 | 250  | 0.5148          | -1.6815        | -2.8054          | 0.7155             | 1.1239          | -528.8192      | -428.1107    | 2.1266          | 1.0144        |
| 0.5           | 0.6857 | 300  | 0.5078          | -1.6879        | -2.8754          | 0.7198             | 1.1875          | -535.8170      | -428.7552    | 2.7028          | 1.5160        |
| 0.4879        | 0.8    | 350  | 0.5050          | -1.8872        | -3.0745          | 0.7198             | 1.1873          | -555.7252      | -448.6785    | 3.2477          | 2.2065        |
| 0.5082        | 0.9143 | 400  | 0.5012          | -1.7553        | -2.9981          | 0.7198             | 1.2428          | -548.0841      | -435.4877    | 3.0596          | 1.9658        |


### Framework versions

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