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whisper-small-es-v3 – AI Model by josebruzzoni | AlphaNeural AI
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whisper-small-es-v3
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transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-small
finetune
apache-2.0
endpoints_compatible
us
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whisper-small-es-v3
This model is a fine-tuned version of
openai/whisper-small
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.2706
Wer: 56.9793
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
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.2565
0.69
1000
0.2811
75.3519
0.1148
1.39
2000
0.2688
42.8365
0.0473
2.08
3000
0.2701
48.2173
0.0453
2.78
4000
0.2706
56.9793
Framework versions
Transformers 4.32.0.dev0
Pytorch 2.0.1+cu118
Datasets 2.14.3
Tokenizers 0.13.3
