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Speech12 – AI Model by OumaElha | AlphaNeural AI
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OumaElha
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Speech12
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transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
generated_from_trainer
apache-2.0
endpoints_compatible
us
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Model card
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Speech12
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: 1.0053
Wer: 1
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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 5000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
2.8827
3.96
1000
2.8766
1
2.8369
7.92
2000
2.8362
1
1.6725
11.88
3000
1.4849
1
1.2083
15.84
4000
1.0574
1
1.1507
19.8
5000
1.0053
1
Framework versions
Transformers 4.28.0
Pytorch 2.0.1
Datasets 2.13.1
Tokenizers 0.13.3
