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Audiclassification – AI Model by Hemg | AlphaNeural AI
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Hemg
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Audiclassification
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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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Model card
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Audiclassification
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: 2.6586
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: 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: 2
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
0.8
3
2.6586
0.0796
No log
1.6
6
2.6530
0.0708
Framework versions
Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2
