MERT-v1-95M-finetuned-DEAM_stripped_vocals

This model is a fine-tuned version of m-a-p/MERT-v1-95M on the Rehead/DEAM_stripped_vocals dataset.

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: 1
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 8
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	R Squared
No log	0.8889	2	17.3474	-17.908

Framework versions

• Transformers 4.46.3
• Pytorch 2.4.1+cu124
• Datasets 3.1.0
• Tokenizers 0.20.2