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whisper-small-uz – AI Model by azamat45 | AlphaNeural AI
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transformers
tensorboard
safetensors
whisper
automatic-speech-recognition
generated_from_trainer
uz
mozilla-foundation/common_voice_8_0
openai/whisper-small
finetune
apache-2.0
model-index
endpoints_compatible
us
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Whisper Small Uz - Azamat Urinboyev
This model is a fine-tuned version of
openai/whisper-small
on the Common Voice 8.0 dataset. It achieves the following results on the evaluation set:
Loss: 0.3743
Wer: 29.1593
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: 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
0.3146
1.3514
1000
0.4122
35.3898
0.1332
2.7027
2000
0.3529
29.7356
0.0256
4.0541
3000
0.3658
29.2881
0.0134
5.4054
4000
0.3743
29.1593
Framework versions
Transformers 4.40.2
Pytorch 2.1.2
Datasets 2.19.1
Tokenizers 0.19.1