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distill-whisper-small-swahili – AI Model by VinyVan | AlphaNeural AI
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distill-whisper-small-swahili
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transformers
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
hi
mozilla-foundation/common_voice_17_0
openai/whisper-small
finetune
apache-2.0
endpoints_compatible
us
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Whisper Small Hi - Viny Van
This model is a fine-tuned version of
openai/whisper-small
on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
eval_loss: 0.8932
eval_wer_ortho: 54.5805
eval_wer: 45.9341
eval_runtime: 184.3007
eval_samples_per_second: 2.17
eval_steps_per_second: 0.271
epoch: 3.2
step: 400
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 OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 200
training_steps: 1000
mixed_precision_training: Native AMP
Framework versions
Transformers 4.52.4
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.2
