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whisper-medium-eu-cv17 – AI Model by deepdml | AlphaNeural AI
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whisper-medium-eu-cv17
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tensorboard
safetensors
whisper
generated_from_trainer
automatic-speech-recognition
eu
mozilla-foundation/common_voice_17_0
openai/whisper-medium
finetune
apache-2.0
model-index
us
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Whisper Medium eu
This model is a fine-tuned version of
openai/whisper-medium
on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
Loss: 0.1067
Wer: 6.2269
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: 32
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: 5000
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.1766
0.3596
1000
0.1877
12.7130
0.1372
0.7192
2000
0.1370
8.7444
0.0634
1.0787
3000
0.1210
7.2108
0.0558
1.4383
4000
0.1119
6.5411
0.0631
1.7979
5000
0.1067
6.2269
Framework versions
Transformers 4.42.0.dev0
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1
