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whisper-base-nl – AI Model by GerwinVanGiessen | AlphaNeural AI
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whisper-base-nl
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
nl
mozilla-foundation/common_voice_13_0
openai/whisper-base
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper Base NL
This model is a fine-tuned version of
openai/whisper-base
on the Common Voice 13.0 dataset. It achieves the following results on the evaluation set:
Loss: 0.3354
Wer: 20.4818
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: 16
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: 4000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.294
0.3734
1000
0.4016
24.5123
0.216
0.7468
2000
0.3617
22.3141
0.1437
1.1202
3000
0.3424
21.1733
0.1299
1.4937
4000
0.3354
20.4818
Framework versions
Transformers 4.42.0.dev0
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1
