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Audioclasswindows – AI Model by Hemg | AlphaNeural AI
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Hemg
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Audioclasswindows
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transformers
tensorboard
safetensors
wav2vec2
audio-classification
generated_from_trainer
minds14
facebook/wav2vec2-base
finetune
apache-2.0
model-index
endpoints_compatible
us
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Audioclasswindows
This model is a fine-tuned version of
facebook/wav2vec2-base
on the minds14 dataset. It achieves the following results on the evaluation set:
Loss: 2.6453
Accuracy: 0.0796
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: 0.0003
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 4
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
2.6426
0.98
14
2.6541
0.0796
2.6524
1.96
28
2.6401
0.0796
2.6346
2.95
42
2.6441
0.0796
2.6325
3.93
56
2.6453
0.0796
Framework versions
Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2
