---
base_model: dynamofl/dynamo-1.6B-v0.4-mosaic
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- snorkelai/Snorkel-Mistral-PairRM-DPO-Dataset
model-index:
- name: outputs-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. -->

# outputs-dpo

This model is a fine-tuned version of [dynamofl/dynamo-1.6B-v0.4-mosaic](https://huggingface.co/dynamofl/dynamo-1.6B-v0.4-mosaic) on the snorkelai/Snorkel-Mistral-PairRM-DPO-Dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5811
- Rewards/chosen: -0.5596
- Rewards/rejected: -0.9329
- Rewards/accuracies: 0.7964
- Rewards/margins: 0.3733
- Logps/rejected: -549.6418
- Logps/chosen: -503.2280
- Logits/rejected: 15.4763
- Logits/chosen: 15.8957

## 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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 6
- gradient_accumulation_steps: 16
- total_train_batch_size: 96
- total_eval_batch_size: 6
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results



### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.15.2