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whisper-small-Cantonese-fine-tune – AI Model by FunPang | AlphaNeural AI
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FunPang
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whisper-small-Cantonese-fine-tune
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-small
finetune
apache-2.0
endpoints_compatible
us
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whisper-small-Cantonese-fine-tune
This model is a fine-tuned version of
openai/whisper-small
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.2485
Wer: 100.0
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: 5e-05
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 5
training_steps: 200
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0003
25.0
100
0.2444
100.0
0.0001
50.0
200
0.2485
100.0
Framework versions
Transformers 4.45.0.dev0
Pytorch 2.4.0+cu118
Datasets 2.21.0
Tokenizers 0.19.1
