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whisper-small-et – AI Model by SaulGoodmens | AlphaNeural AI
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whisper-small-et
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
hf-asr-leaderboard
generated_from_trainer
et
mozilla-foundation/common_voice_11_0
openai/whisper-small
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper Small Et - Hendrik
This model is a fine-tuned version of
openai/whisper-small
on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
Loss: 1.4159
Wer: 72.2628
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: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
training_steps: 500
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.2196
6.67
100
1.3895
71.5328
0.0018
13.33
200
1.3312
69.7080
0.0008
20.0
300
1.3874
71.8978
0.0006
26.67
400
1.4088
72.2628
0.0005
33.33
500
1.4159
72.2628
Framework versions
Transformers 4.39.0.dev0
Pytorch 2.1.0+cu121
Datasets 2.18.0
Tokenizers 0.15.2
