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whisper-small-google_fleurs – AI Model by ibrahimchristopher | AlphaNeural AI
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whisper-small-google_fleurs
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
ha
google/fleurs
openai/whisper-small
finetune
apache-2.0
model-index
endpoints_compatible
us
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FLEURS Finetuned Whisper Small - Ibrahim Ibrahim
This model is a fine-tuned version of
openai/whisper-small
on the Google FLEURS dataset. It achieves the following results on the evaluation set:
Loss: 0.7191
Wer Ortho: 36.6759
Wer: 35.7746
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: 16
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 50
training_steps: 500
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer Ortho
Wer
0.1213
3.2680
500
0.7191
36.6759
35.7746
Framework versions
Transformers 4.46.2
Pytorch 2.5.1+cu121
Datasets 3.1.0
Tokenizers 0.20.3
