---
license: apache-2.0
library_name: peft
tags:
- trl
- dpo
- generated_from_trainer
base_model: alignment-handbook/zephyr-7b-sft-full
model-index:
- name: vanilla_doff_dpo_iter_2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# vanilla_doff_dpo_iter_2

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: 0.6693
- Rewards/chosen: -0.1884
- Rewards/rejected: -0.2428
- Rewards/accuracies: 0.5520
- Rewards/margins: 0.0543
- Logps/rejected: -294.6735
- Logps/chosen: -310.7413
- Logits/rejected: -2.5815
- Logits/chosen: -2.6792

## 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-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- total_eval_batch_size: 8
- 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        | 0.65  | 100  | 0.6693          | -0.1884        | -0.2428          | 0.5520             | 0.0543          | -294.6735      | -310.7413    | -2.5815         | -2.6792       |


### Framework versions

- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2