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ft-whisper-large-v2-audioscorrigidos_2 – AI Model by guilhermebastos96 | AlphaNeural AI
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ft-whisper-large-v2-audioscorrigidos_2
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-large-v2
finetune
apache-2.0
endpoints_compatible
us
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ft-whisper-large-v2-audioscorrigidos_2
This model is a fine-tuned version of
openai/whisper-large-v2
on an unknown dataset. It achieves the following results on the evaluation set:
eval_loss: 1.1441
eval_wer: 32.6136
eval_runtime: 17.5177
eval_samples_per_second: 1.37
eval_steps_per_second: 0.171
epoch: 416.6667
step: 5000
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: 8
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: 10000
mixed_precision_training: Native AMP
Framework versions
Transformers 4.45.2
Pytorch 2.2.1
Datasets 3.0.1
Tokenizers 0.20.1
