---
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-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-prometheus-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: 0.4890
- Rewards/chosen: -1.5856
- Rewards/rejected: -2.7832
- Rewards/accuracies: 0.7371
- Rewards/margins: 1.1976
- Logps/rejected: -526.5942
- Logps/chosen: -418.5211
- Logits/rejected: 3.6380
- Logits/chosen: 2.5080

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6615        | 0.1143 | 50   | 0.6475          | -0.0448        | -0.1732          | 0.6595             | 0.1284          | -265.5944      | -264.4379    | -2.5754         | -2.6221       |
| 0.5507        | 0.2286 | 100  | 0.5504          | -0.7596        | -1.5622          | 0.6897             | 0.8026          | -404.4943      | -335.9164    | 0.2567          | -0.1843       |
| 0.521         | 0.3429 | 150  | 0.5234          | -0.9406        | -1.8921          | 0.7198             | 0.9516          | -437.4890      | -354.0176    | 1.8188          | 1.1097        |
| 0.5162        | 0.4571 | 200  | 0.5108          | -1.2309        | -2.2537          | 0.7328             | 1.0228          | -473.6453      | -383.0527    | 2.2567          | 1.2299        |
| 0.5186        | 0.5714 | 250  | 0.5027          | -1.3697        | -2.4832          | 0.7026             | 1.1135          | -496.5983      | -396.9323    | 2.8322          | 1.5762        |
| 0.4883        | 0.6857 | 300  | 0.4936          | -1.5404        | -2.7021          | 0.7371             | 1.1617          | -518.4875      | -413.9998    | 3.3276          | 2.1394        |
| 0.4714        | 0.8    | 350  | 0.4907          | -1.5101        | -2.6852          | 0.7457             | 1.1752          | -516.7975      | -410.9666    | 3.5416          | 2.3945        |
| 0.4977        | 0.9143 | 400  | 0.4890          | -1.5856        | -2.7832          | 0.7371             | 1.1976          | -526.5942      | -418.5211    | 3.6380          | 2.5080        |


### Framework versions

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