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whisper-tiny – AI Model by Joserzapata | AlphaNeural AI
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Joserzapata
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whisper-tiny
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transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
generated_from_trainer
PolyAI/minds14
apache-2.0
model-index
endpoints_compatible
us
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whisper-tiny
This model is a fine-tuned version of
openai/whisper-tiny
on the PolyAI/minds14 dataset. It achieves the following results on the evaluation set:
Loss: 0.6844
Wer Ortho: 0.3424
Wer: 0.3394
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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 50
training_steps: 500
Training results
Training Loss
Epoch
Step
Validation Loss
Wer Ortho
Wer
0.0006
17.86
500
0.6844
0.3424
0.3394
Framework versions
Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3
