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whisper-canadian-finetune – AI Model by lutskivd | AlphaNeural AI
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whisper-canadian-finetune
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
hf-asr-leaderboard
generated_from_trainer
en
Canadian_english
openai/whisper-tiny
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper tiny Canadian
This model is a fine-tuned version of
openai/whisper-tiny
on the Canadian English dataset. It achieves the following results on the evaluation set:
Loss: 0.4252
Wer: 20.7710
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: 2
eval_batch_size: 1
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: 2000
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.3024
1.0
1000
0.4231
21.4529
0.1132
2.0
2000
0.4252
20.7710
Framework versions
Transformers 4.50.0.dev0
Pytorch 2.5.1+cu124
Datasets 3.3.2
Tokenizers 0.21.0
