---
library_name: transformers
base_model: data/OpenELM-1_1B-SFT
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: OpenELM-1_1B-DPO-2
  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. -->

# OpenELM-1_1B-DPO-2

This model is a fine-tuned version of [data/OpenELM-1_1B-SFT](https://huggingface.co/data/OpenELM-1_1B-SFT) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7793
- Rewards/chosen: -11.75
- Rewards/rejected: -13.6875
- Rewards/accuracies: 0.7227
- Rewards/margins: 1.9141
- Logps/rejected: -564.0
- Logps/chosen: -556.0
- Logits/rejected: -13.0625
- Logits/chosen: -13.3125

## 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-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6791        | 1.0   | 1911 | 0.7098          | -10.8125       | -11.9375         | 0.6992             | 1.1328          | -528.0         | -536.0       | -12.5625        | -12.6875      |
| 0.0506        | 2.0   | 3822 | 0.7793          | -11.75         | -13.6875         | 0.7227             | 1.9141          | -564.0         | -556.0       | -13.0625        | -13.3125      |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.3.0
- Datasets 2.21.0
- Tokenizers 0.19.1