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whisper-base-de – AI Model by Krish03 | AlphaNeural AI | AlphaNeural AI
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whisper-base-de
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
de
mozilla-foundation/common_voice_11_0
openai/whisper-base
finetune
apache-2.0
model-index
endpoints_compatible
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Whisper Base De - Krish Kalra
This model is a fine-tuned version of
openai/whisper-base
on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
Loss: 0.4592
Wer: 24.2481
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: Use OptimizerNames.ADAMW_TORCH 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: 5
num_epochs: 5
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.4712
1.0
283
0.4442
26.1604
0.46
2.0
566
0.4376
23.1155
0.1985
3.0
849
0.4449
28.6669
0.1576
4.0
1132
0.4542
24.2852
0.0695
5.0
1415
0.4592
24.2481
Framework versions
Transformers 4.46.2
Pytorch 2.5.1+cu124
Datasets 3.1.0
Tokenizers 0.20.3
