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whisper-base-wolof – AI Model by serge-wilson | AlphaNeural AI
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whisper-base-wolof
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transformers
pytorch
whisper
automatic-speech-recognition
generated_from_trainer
multilingual
openai/whisper-base
finetune
apache-2.0
endpoints_compatible
us
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Whisper Base Wolof
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: 0.2902
Wer: 32.8385
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
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.5632
1.14
1000
0.4672
48.8263
0.3464
2.29
2000
0.3461
34.6403
0.2514
3.43
3000
0.3013
32.1406
0.1957
4.57
4000
0.2902
32.8385
Framework versions
Transformers 4.34.0.dev0
Pytorch 2.0.0
Datasets 2.14.5
Tokenizers 0.13.3
