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whisper-small-wolof – AI Model by ngia | AlphaNeural AI
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whisper-small-wolof
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
wo
IndabaxSenegal/asr-wolof-dataset
openai/whisper-small
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper small Wolof
This model is a fine-tuned version of
openai/whisper-small
on the ASR Wolof Dataset dataset. It achieves the following results on the evaluation set:
Loss: 1.1760
Wer: 51.2109
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
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
num_epochs: 2
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0367
1.0
450
1.1685
50.4807
0.0191
2.0
900
1.1760
51.2109
Framework versions
Transformers 4.46.3
Pytorch 2.4.0
Datasets 3.1.0
Tokenizers 0.20.0
