---
tags:
- trl
- dpo
- generated_from_trainer
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 was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4292
- Rewards/chosen: -1.8869
- Rewards/rejected: -2.7914
- Rewards/accuracies: 0.8242
- Rewards/margins: 0.9045
- Logps/rejected: -612.2493
- Logps/chosen: -524.2042
- Logits/rejected: -0.4436
- Logits/chosen: -0.8025

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5405        | 0.12  | 100  | 0.6086          | -0.8599        | -1.1867          | 0.6953             | 0.3268          | -451.7755      | -421.5048    | -1.6547         | -1.7462       |
| 0.4371        | 0.23  | 200  | 0.5454          | -2.0208        | -2.5842          | 0.7422             | 0.5634          | -591.5291      | -537.5920    | -0.7151         | -0.8867       |
| 0.4348        | 0.35  | 300  | 0.5012          | -2.0998        | -2.8410          | 0.7734             | 0.7413          | -617.2101      | -545.4883    | -0.3499         | -0.5939       |
| 0.3733        | 0.46  | 400  | 0.4721          | -2.1506        | -2.9308          | 0.7773             | 0.7802          | -626.1902      | -550.5717    | -0.2280         | -0.5456       |
| 0.3689        | 0.58  | 500  | 0.4484          | -2.0467        | -2.9485          | 0.7969             | 0.9018          | -627.9595      | -540.1826    | -0.1091         | -0.4774       |
| 0.3829        | 0.69  | 600  | 0.4419          | -2.0265        | -2.9075          | 0.8086             | 0.8810          | -623.8541      | -538.1624    | -0.1412         | -0.5099       |
| 0.3725        | 0.81  | 700  | 0.4329          | -1.9184        | -2.8079          | 0.8242             | 0.8895          | -613.8932      | -527.3496    | -0.3224         | -0.6920       |
| 0.4052        | 0.92  | 800  | 0.4292          | -1.8869        | -2.7914          | 0.8242             | 0.9045          | -612.2493      | -524.2042    | -0.4436         | -0.8025       |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.2