---
license: other
base_model: apple/OpenELM-270M
tags:
- trl
- orpo
- generated_from_trainer
model-index:
- name: ft-openelm-270m-ultrafeedback
  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. -->

# ft-openelm-270m-ultrafeedback

This model is a fine-tuned version of [apple/OpenELM-270M](https://huggingface.co/apple/OpenELM-270M) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6455
- Rewards/chosen: -0.1995
- Rewards/rejected: -0.2029
- Rewards/accuracies: 0.5050
- Rewards/margins: 0.0035
- Logps/rejected: -2.0293
- Logps/chosen: -1.9941
- Logits/rejected: -5.7383
- Logits/chosen: -6.1055
- Nll Loss: 1.5752
- Log Odds Ratio: -0.7037
- Log Odds Chosen: 0.0445

## 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: 8e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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 | Nll Loss | Log Odds Ratio | Log Odds Chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
| 1.7595        | 0.53  | 100  | 1.6455          | -0.1995        | -0.2029          | 0.5050             | 0.0035          | -2.0293        | -1.9941      | -5.7383         | -6.1055       | 1.5752   | -0.7037        | 0.0445          |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2