Whisper medium Sw2 - Kiazi Bora
This model is a fine-tuned version of
openai/whisper-medium
on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
-
Loss: 0.4788
-
Wer: 32.9689
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: 16
-
eval_batch_size: 8
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seed: 42
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optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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lr_scheduler_type: linear
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lr_scheduler_warmup_steps: 500
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training_steps: 2000
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mixed_precision_training: Native AMP
Training results
Training Loss
|
Epoch
|
Step
|
Validation Loss
|
Wer
|
0.4257
|
0.43
|
1000
|
0.5451
|
36.7129
|
0.3494
|
0.87
|
2000
|
0.4788
|
32.9689
|
Framework versions
-
Transformers 4.26.0.dev0
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Pytorch 1.13.0+cu116
-
Datasets 2.7.1
-
Tokenizers 0.13.2