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whisper-base-finetuned-gtzan – AI Model by b-koopman | AlphaNeural AI
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b-koopman
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whisper-base-finetuned-gtzan
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transformers
pytorch
tensorboard
whisper
audio-classification
generated_from_trainer
marsyas/gtzan
apache-2.0
endpoints_compatible
us
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whisper-base-finetuned-gtzan
This model is a fine-tuned version of
openai/whisper-base
on the GTZAN dataset. It achieves the following results on the evaluation set:
Loss: 0.3910
Accuracy: 0.88
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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.8923
1.0
113
0.7722
0.74
0.8088
2.0
226
0.6883
0.78
0.3561
3.0
339
0.7117
0.78
0.0312
4.0
452
0.4188
0.88
0.0108
5.0
565
0.3910
0.88
Framework versions
Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3
