Beta
Explore
Marketplace
Neural Labs
Chat
Wallet
Docs
wav2vec2-base-finetuned-stop-classification – AI Model by suyuanliu | AlphaNeural AI
You can deploy this model and start earning money today!
suyuanliu
/
wav2vec2-base-finetuned-stop-classification
like
0
transformers
pytorch
wav2vec2
audio-classification
generated_from_trainer
audiofolder
apache-2.0
endpoints_compatible
us
Views
No views yet
Model card
Files and Versions
Community
API
Deploy
wav2vec2-base-finetuned-stop-classification
This model is a fine-tuned version of
facebook/wav2vec2-base
on the audiofolder dataset. It achieves the following results on the evaluation set:
Loss: 0.1647
Accuracy: 0.9470
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: 64
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.671
0.98
26
0.5553
0.8347
0.3525
1.98
52
0.2647
0.9163
0.291
2.98
78
0.2474
0.9070
0.2733
3.98
104
0.1729
0.9439
0.2467
4.98
130
0.1647
0.9470
Framework versions
Transformers 4.25.1
Pytorch 1.13.0
Datasets 2.7.1
Tokenizers 0.13.2
