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HuBERT-base-libriSpeech-demo-colab – AI Model by vishwasgautam | AlphaNeural AI
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vishwasgautam
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HuBERT-base-libriSpeech-demo-colab
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transformers
pytorch
tensorboard
hubert
automatic-speech-recognition
generated_from_trainer
apache-2.0
endpoints_compatible
us
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HuBERT-base-libriSpeech-demo-colab
This model is a fine-tuned version of
facebook/hubert-large-ls960-ft
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1456
Wer: 0.2443
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: 2
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: 1000
num_epochs: 30
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
7.6395
13.51
500
3.1933
0.9930
2.5994
27.03
1000
0.1456
0.2443
Framework versions
Transformers 4.20.1
Pytorch 1.11.0+cu113
Datasets 2.3.2
Tokenizers 0.12.1
