metadata

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

ft-openelm-270m-ultrafeedback

This model is a fine-tuned version of apple/OpenELM-270M on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:

Loss: 1.6455
Rewards/chosen: -0.1993
Rewards/rejected: -0.2029
Rewards/accuracies: 0.5050
Rewards/margins: 0.0035
Logps/rejected: -2.0273
Logps/chosen: -1.9941
Logits/rejected: -5.7383
Logits/chosen: -6.1094
Nll Loss: 1.5742
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
1.7594	0.53	100	1.6455	-0.1993	-0.2029	0.5050	0.0035	-2.0273	-1.9941	-5.7383	-6.1094	1.5742	-0.7037	0.0445

Framework versions

Transformers 4.39.3
Pytorch 2.4.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2