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wav2vec2-base-ks-2sec – AI Model by alirezafarashah | AlphaNeural AI
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wav2vec2-base-ks-2sec
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transformers
pytorch
tensorboard
wav2vec2
audio-classification
generated_from_trainer
superb
apache-2.0
endpoints_compatible
us
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wav2vec2-base-ks-2sec
This model is a fine-tuned version of
facebook/wav2vec2-base
on the superb dataset. It achieves the following results on the evaluation set:
Loss: 0.0880
Accuracy: 0.9822
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: 5
Training results
Training Loss
Epoch
Step
Accuracy
Validation Loss
0.5003
1.0
399
0.9643
0.4284
0.1868
2.0
798
0.9748
0.1628
0.1413
3.0
1197
0.9796
0.1128
0.1021
4.0
1596
0.9813
0.0940
0.1089
5.0
1995
0.0880
0.9822
Framework versions
Transformers 4.11.3
Pytorch 1.10.0+cu111
Datasets 1.14.0
Tokenizers 0.10.3
