README.md

metadata

language:
  - uz
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_16_1
metrics:
  - wer
model-index:
  - name: Whisper Small UZ - Bahriddin Mo'minov
    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: 28.692515325042255

Whisper Small UZ - Bahriddin Mo'minov

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

• Loss: 0.3379
• Wer: 28.6925

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
0.5499	0.2641	1000	0.5142	39.8375
0.4419	0.5281	2000	0.4080	33.3644
0.3506	0.7922	3000	0.3544	29.7293
0.242	1.0562	4000	0.3379	28.6925

Framework versions

• Transformers 4.41.0
• Pytorch 2.2.2+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1