---
license: apache-2.0
base_model: decapoda-research/Adrastea-7b-v1.0
tags:
- generated_from_trainer
model-index:
- name: zephyr-7b-dpo-lora
  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-lora

This model is a fine-tuned version of [decapoda-research/Adrastea-7b-v1.0](https://huggingface.co/decapoda-research/Adrastea-7b-v1.0) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6086
- Rewards/chosen: 0.1339
- Rewards/rejected: -0.0905
- Rewards/accuracies: 0.6976
- Rewards/margins: 0.2244
- Logps/rejected: -260.8578
- Logps/chosen: -297.0598
- Logits/rejected: -3.6473
- Logits/chosen: -3.5958

## 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: 2
- eval_batch_size: 4
- seed: 420
- distributed_type: multi-GPU
- num_devices: 3
- gradient_accumulation_steps: 32
- total_train_batch_size: 192
- total_eval_batch_size: 12
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6101        | 1.0   | 322  | 0.6086          | 0.1339         | -0.0905          | 0.6976             | 0.2244          | -260.8578      | -297.0598    | -3.6473         | -3.5958       |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.1+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1