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whisper-base-google-fleurs-pt-br – AI Model by thiagobarbosa | AlphaNeural AI
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thiagobarbosa
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whisper-base-google-fleurs-pt-br
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transformers
pytorch
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-base
finetune
apache-2.0
endpoints_compatible
us
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whisper-base-google-fleurs-pt-br
This model is a fine-tuned version of
openai/whisper-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.4987
Wer: 22.2974
Wer Normalized: 18.5291
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: 2.05e-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: reduce_lr_on_plateau
lr_scheduler_warmup_steps: 120
training_steps: 2400
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
Wer Normalized
0.3716
1.01
400
0.3988
21.8039
17.8916
0.2003
2.02
800
0.4440
22.3350
18.6242
0.0571
3.02
1200
0.4960
22.5982
19.2284
0.03
4.03
1600
0.4987
22.2974
18.5291
Framework versions
Transformers 4.36.2
Pytorch 2.1.1
Datasets 2.16.1
Tokenizers 0.15.0
