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whisper-medium-uz_v1 – AI Model by blackhole33 | AlphaNeural AI
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whisper-medium-uz_v1
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transformers
pytorch
whisper
automatic-speech-recognition
generated_from_trainer
uz
mozilla-foundation/common_voice_17_0
openai/whisper-medium
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper Medium UZB
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: 0.2859
Wer: 31.7790
Model description
More information needed
Intended uses & limitations
More information needed
Founder: Rifat Mamayusupov
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
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: 500
training_steps: 4000
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Wer
0.5187
0.5392
1000
0.4935
44.1403
0.3423
1.0785
2000
0.4008
37.6948
0.3018
1.6177
3000
0.3739
36.3575
0.2401
2.1569
4000
0.2821
31.7791
Framework versions
Transformers 4.41.2
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1
