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whisper-base-cs-cv11-rir-vol-bckgnoise-lowshelf-mp3 – AI Model by LadislavVasina1 | AlphaNeural AI
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LadislavVasina1
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whisper-base-cs-cv11-rir-vol-bckgnoise-lowshelf-mp3
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-base
finetune
apache-2.0
endpoints_compatible
us
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whisper-base-cs-cv11-rir-vol-bckgnoise-lowshelf-mp3
This model is a fine-tuned version of
openai/whisper-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.3720
Wer: 36.1126
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: 4
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 4000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.663
1.44
1000
0.4620
45.0529
0.4758
2.89
2000
0.3914
38.3394
0.3063
4.33
3000
0.3759
36.7573
0.2793
5.78
4000
0.3720
36.1126
Framework versions
Transformers 4.36.2
Pytorch 2.1.0+cu121
Datasets 2.15.0
Tokenizers 0.15.0
