---
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: 1.3947
- Rewards/chosen: -2.4314
- Rewards/rejected: -2.0023
- Rewards/accuracies: 0.3867
- Rewards/margins: -0.4292
- Logps/rejected: -517.7516
- Logps/chosen: -554.9180
- Logits/rejected: -1.0823
- Logits/chosen: -1.1239

## 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 | Logits/chosen | Logits/rejected | Logps/chosen | Logps/rejected | Validation Loss | Rewards/accuracies | Rewards/chosen | Rewards/margins | Rewards/rejected |
|:-------------:|:-----:|:----:|:-------------:|:---------------:|:------------:|:--------------:|:---------------:|:------------------:|:--------------:|:---------------:|:----------------:|
| 0.3047        | 0.1   | 100  | -2.4405       | -2.3863         | -361.0801    | -337.7748      | 0.8551          | 0.3203             | -0.4930        | -0.2905         | -0.2025          |
| 0.1861        | 0.21  | 200  | -1.5418       | -1.5107         | -450.2716    | -421.0934      | 1.0495          | 0.3867             | -1.3850        | -0.3493         | -1.0357          |
| 0.1608        | 0.31  | 300  | -1.4367       | -1.4022         | -454.9446    | -422.9684      | 1.0910          | 0.3945             | -1.4317        | -0.3772         | -1.0544          |
| 0.1368        | 0.42  | 400  | -1.0538       | -1.0131         | -520.1699    | -479.6456      | 1.3010          | 0.4102             | -2.0839        | -0.4627         | -1.6212          |
| 0.1364        | 0.52  | 500  | -1.6466       | -1.6090         | -470.0934    | -430.8614      | 1.1773          | 0.3711             | -1.5832        | -0.4498         | -1.1334          |
| 0.1223        | 0.63  | 600  | 1.3206        | -2.2971         | -1.8297      | 0.4141         | -0.4674         | -500.4930          | -541.4883      | -1.1541         | -1.1880          |
| 0.0971        | 0.73  | 700  | 1.4638        | -2.6554         | -2.1594      | 0.3906         | -0.4959         | -533.4667          | -577.3128      | -0.9392         | -0.9712          |
| 0.1035        | 0.84  | 800  | 1.4475        | -2.5761         | -2.1538      | 0.3945         | -0.4222         | -532.9068          | -569.3817      | -0.8902         | -0.9232          |
| 0.088         | 0.94  | 900  | 1.3947        | -2.4314         | -2.0023      | 0.3867         | -0.4292         | -517.7516          | -554.9180      | -1.0823         | -1.1239          |


### Framework versions

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