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whisper-tiny_tat_vanilla_evaluated_on_XYH-6-X – AI Model by jethrowang | AlphaNeural AI
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whisper-tiny_tat_vanilla_evaluated_on_XYH-6-X
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
zh
formospeech/tat_asr_aligned
openai/whisper-tiny
finetune
apache-2.0
endpoints_compatible
us
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Whisper Tiny Taiwanese Condenser
This model is a fine-tuned version of
openai/whisper-tiny
on the TAT ASR Aligned dataset. It achieves the following results on the evaluation set:
eval_loss: 0.6412
eval_model_preparation_time: 0.0032
eval_cer: 11.9582
eval_runtime: 1540.2845
eval_samples_per_second: 3.646
eval_steps_per_second: 0.114
step: 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: 0.0001
train_batch_size: 64
eval_batch_size: 32
seed: 42
optimizer: Use 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: 681
training_steps: 6810
mixed_precision_training: Native AMP
Framework versions
Transformers 4.49.0
Pytorch 2.0.0.post304
Datasets 3.3.2
Tokenizers 0.21.0
