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wav2vec2-xlsr-53-espeak-cv-ft-bak2-ntsema-colab – AI Model by ntsema | AlphaNeural AI
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ntsema
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wav2vec2-xlsr-53-espeak-cv-ft-bak2-ntsema-colab
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transformers
pytorch
tensorboard
wav2vec2
automatic-speech-recognition
generated_from_trainer
audiofolder
apache-2.0
model-index
endpoints_compatible
us
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wav2vec2-xlsr-53-espeak-cv-ft-bak2-ntsema-colab
This model is a fine-tuned version of
ntsema/wav2vec2-xlsr-53-espeak-cv-ft-tat-ntsema-colab
on the audiofolder dataset. It achieves the following results on the evaluation set:
Loss: inf
Wer: 1.0778
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: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 30
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
1.1586
8.33
400
inf
1.0029
0.3107
16.66
800
inf
1.0202
0.1534
24.99
1200
inf
1.0778
Framework versions
Transformers 4.24.0
Pytorch 1.12.1+cu113
Datasets 2.6.1
Tokenizers 0.13.2
