metadata

library_name: transformers
language:
  - uz
license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_16_1
metrics:
  - wer
model-index:
  - name: Whisper Tiny UZ - Bahriddin Muminov
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 16.1
          type: mozilla-foundation/common_voice_16_1
          config: uz
          split: test
          args: 'config: uz, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 50.19916836282356

Whisper Tiny UZ - Bahriddin Muminov

This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 16.1 dataset. It achieves the following results on the evaluation set:

Loss: 0.5943
Wer: 50.1992

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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
training_steps: 10000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.6528	0.0352	2000	0.8591	62.8798
0.5201	0.0704	4000	0.7052	56.4951
0.4258	0.1056	6000	0.6407	53.7817
0.4136	0.1408	8000	0.6057	50.5588
0.4164	0.1760	10000	0.5943	50.1992

Framework versions

Transformers 4.49.0
Pytorch 2.6.0+cu124
Datasets 3.4.1
Tokenizers 0.21.1