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whisper-medium-zh-tw – AI Model by DDTChen | AlphaNeural AI
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whisper-medium-zh-tw
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
hf-asr-leaderboard
generated_from_trainer
zh
mozilla-foundation/common_voice_11_0
openai/whisper-medium
finetune
apache-2.0
endpoints_compatible
us
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whisper-medium-zh-tw
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: 0.1739
Cer: 7.0715
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
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 4000
Training results
Training Loss
Epoch
Step
Validation Loss
Cer
0.0675
1.4184
1000
0.1620
8.3479
0.0219
2.8369
2000
0.1692
8.3796
0.0009
4.2553
3000
0.1699
7.1349
0.0006
5.6738
4000
0.1739
7.0715
Framework versions
Transformers 4.51.1
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1
