---
license: other
base_model: Columbia-NLP/gemma-2b-zephyr-sft
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- alignment-handbook
- generated_from_trainer
datasets:
- argilla/dpo-mix-7k
model-index:
- name: zephyr-7b-gemma-dpo
  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-gemma-dpo

This model is a fine-tuned version of [Columbia-NLP/gemma-2b-zephyr-sft](https://huggingface.co/Columbia-NLP/gemma-2b-zephyr-sft) on the argilla/dpo-mix-7k dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5964
- Rewards/chosen: 0.3541
- Rewards/rejected: 0.1118
- Rewards/accuracies: 0.6562
- Rewards/margins: 0.2424
- Logps/rejected: -373.3665
- Logps/chosen: -371.9911
- Logits/rejected: -12.6656
- Logits/chosen: -13.2953

## 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: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.5732        | 1.8957 | 100  | 0.5972          | 0.3534         | 0.1096           | 0.6771             | 0.2437          | -373.4094      | -372.0067    | -12.6654        | -13.2926      |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.1.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1