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
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Model tree for dekelzak/MERT-v1-95M-finetuned-DEAM_stripped_vocals
Base model
m-a-p/MERT-v1-95M