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whisper-base-en-atc – AI Model by jkornoff | AlphaNeural AI
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whisper-base-en-atc
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transformers
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
openai/whisper-base.en
finetune
apache-2.0
endpoints_compatible
us
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whisper-base-en-atc
This model is a fine-tuned version of
openai/whisper-base.en
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 2.9906
Wer: 1.7584
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: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 100
num_epochs: 1
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.5561
0.2688
250
2.9956
1.5391
0.3877
0.5376
500
2.9964
1.8011
0.3324
0.8065
750
2.9906
1.7584
Framework versions
Transformers 5.3.0
Pytorch 2.10.0+cu130
Datasets 4.7.0
Tokenizers 0.22.2
