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whisper-small-cantonese – AI Model by Marco-Cheung | AlphaNeural AI
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whisper-small-cantonese
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transformers
pytorch
whisper
automatic-speech-recognition
generated_from_trainer
zh
mozilla-foundation/common_voice_13_0
openai/whisper-small
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper Small Cantonese - Marco Cheung
This model is a fine-tuned version of
openai/whisper-small
on the Common Voice 13 dataset. It achieves the following results on the evaluation set:
Loss: 0.2487
Wer Ortho: 57.8423
Wer: 57.7008
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: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 10
training_steps: 2000
Training results
Training Loss
Epoch
Step
Validation Loss
Wer Ortho
Wer
0.1621
1.14
1000
0.2587
61.0824
65.0094
0.0767
2.28
2000
0.2487
57.8423
57.7008
Framework versions
Transformers 4.32.0.dev0
Pytorch 2.0.1+cu117
Datasets 2.14.3
Tokenizers 0.13.3
