simpo-oh_teknium_scaling_down_ratiocontrolled_0.9

This model is a fine-tuned version of mlfoundations-dev/oh_teknium_scaling_down_ratiocontrolled_0.9 on the mlfoundations-dev/gemma2-ultrafeedback-armorm dataset. It achieves the following results on the evaluation set:

• Loss: 2.9107
• Rewards/chosen: -28.4962
• Rewards/rejected: -33.8743
• Rewards/accuracies: 0.7604
• Rewards/margins: 5.3780
• Logps/chosen: -2.8496
• Logps/rejected: -3.3874
• Logits/chosen: -1.0682
• Logits/rejected: -1.0625

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-07
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• distributed_type: multi-GPU
• num_devices: 8
• gradient_accumulation_steps: 8
• total_train_batch_size: 128
• total_eval_batch_size: 16
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 1.0

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/chosen	Logps/rejected	Logits/chosen	Logits/rejected
2.7514	0.9997	442	2.9107	-28.4962	-33.8743	0.7604	5.3780	-2.8496	-3.3874	-1.0682	-1.0625

Framework versions

• Transformers 4.46.1
• Pytorch 2.3.0
• Datasets 3.1.0
• Tokenizers 0.20.3