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whisper-medium-sl – AI Model by shripadbhat | AlphaNeural AI
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whisper-medium-sl
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transformers
pytorch
tensorboard
whisper
automatic-speech-recognition
whisper-event
generated_from_trainer
sl
mozilla-foundation/common_voice_11_0
apache-2.0
model-index
endpoints_compatible
us
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Whisper Medium Slovenian
This model is a fine-tuned version of
openai/whisper-medium
on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
Loss: 0.2653
Wer: 16.8051
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: 32
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
training_steps: 400
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.161
1.33
100
0.2516
21.6149
0.0386
2.66
200
0.2476
18.5979
0.0161
3.99
300
0.2491
17.1841
0.0032
5.33
400
0.2653
16.8051
Framework versions
Transformers 4.26.0.dev0
Pytorch 1.13.0+cu117
Datasets 2.7.1.dev0
Tokenizers 0.13.2
