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base-asr-with-tpbs-cv4 – AI Model by krirk | AlphaNeural AI
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krirk
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base-asr-with-tpbs-cv4
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transformers
pytorch
tensorboard
wav2vec2
automatic-speech-recognition
generated_from_trainer
endpoints_compatible
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base-asr-with-tpbs-cv4
This model is a fine-tuned version of
Botnoi/base-asr-with-lm
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.5538
Wer: 0.2576
Cer: 0.0695
Clean Cer: 0.0599
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: 32
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 100
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
Cer
Clean Cer
0.1306
26.67
400
0.4897
0.2766
0.0733
0.0642
0.0437
53.33
800
0.4923
0.2566
0.0685
0.0596
0.0293
80.0
1200
0.5538
0.2576
0.0695
0.0599
Framework versions
Transformers 4.27.4
Pytorch 1.13.1+cu117
Datasets 2.11.0
Tokenizers 0.13.2
