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wav2vec2-base-splitted-idrak-exp – AI Model by m-aliabbas | AlphaNeural AI
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m-aliabbas
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wav2vec2-base-splitted-idrak-exp
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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-splitted-idrak-exp
This model is a fine-tuned version of
facebook/wav2vec2-base
on the None dataset. It achieves the following results on the evaluation set:
eval_loss: 3.3141
eval_wer: 1.0
eval_runtime: 17.0978
eval_samples_per_second: 34.39
eval_steps_per_second: 4.328
epoch: 4.38
step: 2600
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: 1e-05
train_batch_size: 4
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: 10
mixed_precision_training: Native AMP
Framework versions
Transformers 4.20.1
Pytorch 1.12.0+cu116
Datasets 2.3.2
Tokenizers 0.12.1
