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whisper-base-nl-2 – AI Model by SuperKogito | AlphaNeural AI
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SuperKogito
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whisper-base-nl-2
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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-base-nl-2
This model is a fine-tuned version of
openai/whisper-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.4946
Wer: 25.6740
Cer: 8.4872
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: 2
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: 1500
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
Cer
0.4709
0.12
1000
0.4946
25.6740
8.4872
Framework versions
Transformers 4.26.0.dev0
Pytorch 1.13.1+cu117
Datasets 2.8.1.dev0
Tokenizers 0.13.2
