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whisper-base-es – AI Model by jpalvaradomil | AlphaNeural AI
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whisper-base-es
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
es
mozilla-foundation/common_voice_11_0
openai/whisper-base
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper base - jpalvaradomil
This model is a fine-tuned version of
openai/whisper-base
on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
Loss: 0.3532
Wer: 20.5804
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: 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: 500
training_steps: 4000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.4099
0.0650
1000
0.4080
22.7274
0.365
0.1301
2000
0.3787
21.5316
0.3449
0.1951
3000
0.3614
21.2915
0.3278
0.2602
4000
0.3532
20.5804
Framework versions
Transformers 4.50.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1
