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whisper-en-tiny-trained – AI Model by EducativeCS2023 | AlphaNeural AI
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EducativeCS2023
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whisper-en-tiny-trained
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transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
generated_from_trainer
apache-2.0
endpoints_compatible
us
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whisper-en-tiny-trained
This model is a fine-tuned version of
openai/whisper-tiny
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.4552
Wer: 92.5515
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: 1
eval_batch_size: 1
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
training_steps: 120
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
1.8547
1.0
60
2.0399
100.1585
1.0927
2.0
120
1.4552
92.5515
Framework versions
Transformers 4.29.2
Pytorch 2.0.1+cu117
Datasets 2.12.0
Tokenizers 0.13.3
