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whisper-small-br – AI Model by ArzhurKoadek | AlphaNeural AI
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whisper-small-br
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
br
mozilla-foundation/common_voice_17_0
openai/whisper-small
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper Small Br - Arzhur Koadek
This model is a fine-tuned version of
openai/whisper-small
on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
Loss: 0.9421
Wer: 52.2397
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
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.168
3.2468
1000
0.7951
53.9458
0.0124
6.4935
2000
0.8755
51.6273
0.0016
9.7403
3000
0.9224
52.6509
0.0009
12.9870
4000
0.9421
52.2397
Framework versions
Transformers 4.40.1
Pytorch 2.2.1+cu121
Datasets 2.19.0
Tokenizers 0.19.1
