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prosodic_accuracy – AI Model by JohnJumon | AlphaNeural AI
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JohnJumon
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prosodic_accuracy
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transformers
tensorboard
safetensors
whisper
audio-classification
generated_from_trainer
openai/whisper-base
finetune
apache-2.0
endpoints_compatible
us
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prosodic_accuracy
This model is a fine-tuned version of
openai/whisper-base
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.7194
Accuracy: 0.726
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: 32
eval_batch_size: 32
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
1.0
125
0.7684
0.67
No log
2.0
250
0.6754
0.728
No log
3.0
375
0.7194
0.726
Framework versions
Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2
