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whisper-base-de-puct-4k – AI Model by CheeLi03 | AlphaNeural AI
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whisper-base-de-puct-4k
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
hf-asr-leaderboard
generated_from_trainer
de
fleurs
openai/whisper-base
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper Base German Punctuation 4k - Chee Li
This model is a fine-tuned version of
openai/whisper-base
on the Google Fleurs dataset. It achieves the following results on the evaluation set:
Loss: 0.6091
Wer: 42.6527
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 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: 500
training_steps: 4000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.0578
4.7619
1000
0.4862
36.8202
0.0052
9.5238
2000
0.5652
36.5610
0.0028
14.2857
3000
0.5972
41.4808
0.0023
19.0476
4000
0.6091
42.6527
Framework versions
Transformers 4.46.2
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.20.3
