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fluency_accuracy – AI Model by JohnJumon | AlphaNeural AI | AlphaNeural AI
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fluency_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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fluency_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: 0.5218
Accuracy: 0.827
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
0.4664
0.814
No log
2.0
250
0.4250
0.823
No log
3.0
375
0.5218
0.827
Framework versions
Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2
