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whisper-SV3 – AI Model by SebLih | AlphaNeural AI
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SebLih
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whisper-SV3
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transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
hf-asr-leaderboard
generated_from_trainer
sv
apache-2.0
endpoints_compatible
us
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Whisper Small SV
This model is a fine-tuned version of
openai/whisper-small
on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
Loss: 0.3516
Wer: 23.0598
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: 200
training_steps: 1000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.3274
0.86
200
0.3552
24.7469
0.1395
1.72
400
0.3303
23.5038
0.074
2.59
600
0.3349
22.6603
0.0199
3.45
800
0.3451
22.7935
0.0089
4.31
1000
0.3516
23.0598
Framework versions
Transformers 4.26.0.dev0
Pytorch 1.13.0+cu116
Datasets 2.7.1
Tokenizers 0.13.2
