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MERT-v1-95M-finetuned-DEAM_stripped_vocals – AI Model by dekelzak | AlphaNeural AI
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dekelzak
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MERT-v1-95M-finetuned-DEAM_stripped_vocals
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transformers
safetensors
mert_model
feature-extraction
generated_from_trainer
custom_code
Rehead/DEAM_stripped_vocals
m-a-p/MERT-v1-95M
finetune
cc-by-nc-4.0
us
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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
