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wav2vec2-base-librispeech100h-google-colab – AI Model by zoha | AlphaNeural AI
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zoha
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wav2vec2-base-librispeech100h-google-colab
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transformers
pytorch
tensorboard
wav2vec2
automatic-speech-recognition
generated_from_trainer
apache-2.0
endpoints_compatible
us
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wav2vec2-base-librispeech100h-google-colab
This model is a fine-tuned version of
facebook/wav2vec2-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1156
Wer: 0.0756
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: 0.0001
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
1.6033
0.9
1600
0.4802
0.2728
0.1912
1.79
3200
0.1601
0.1140
0.1409
2.69
4800
0.1423
0.0932
0.108
3.59
6400
0.1260
0.0806
0.1045
4.48
8000
0.1156
0.0756
Framework versions
Transformers 4.20.0.dev0
Pytorch 1.11.0+cu113
Datasets 2.2.3.dev0
Tokenizers 0.12.1
