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whisper – AI Model by khaingsmon | AlphaNeural AI
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whisper
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-tiny.en
finetune
apache-2.0
endpoints_compatible
us
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whisper
This model is a fine-tuned version of
openai/whisper-tiny.en
on the tiny dataset. It achieves the following results on the evaluation set:
Loss: 3.9871
Wer: 83.6108
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: 64
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 10
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
3.965
0.1408
10
3.9871
83.6108
Framework versions
Transformers 4.40.1
Pytorch 2.2.1+cu121
Datasets 2.19.1.dev0
Tokenizers 0.19.1