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wake_word – AI Model by Ahmed-ibn-Harun | AlphaNeural AI
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Ahmed-ibn-Harun
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wake_word
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transformers
tensorboard
safetensors
wav2vec2
audio-classification
generated_from_trainer
wake
facebook/wav2vec2-base
finetune
apache-2.0
model-index
endpoints_compatible
us
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wake_word
This model is a fine-tuned version of
facebook/wav2vec2-base
on the wake dataset. It achieves the following results on the evaluation set:
Loss: 0.0000
Accuracy: 1.0
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: 3e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.0
1.0
107
0.0000
1.0
Framework versions
Transformers 4.35.0
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1
