README.md

metadata

base_model: openai/whisper-small
datasets:
  - mozilla-foundation/common_voice_17_0
language:
  - uz
library_name: transformers
license: apache-2.0
metrics:
  - wer
tags:
  - generated_from_trainer
model-index:
  - name: Whisper Small Uz - Doniyor Halilov
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: Common Voice 17.0
          type: mozilla-foundation/common_voice_17_0
          config: uz
          split: test
          args: 'config: uz, split: test'
        metrics:
          - type: wer
            value: 54.74920162871594
            name: Wer

Whisper Small Uz - Doniyor Halilov

This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:

• Loss: 1.0147
• Wer: 54.7492

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: 1
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 8
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 100
• training_steps: 200
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.612	0.0132	100	1.2551	69.5533
1.1271	0.0264	200	1.0147	54.7492

Framework versions

• Transformers 4.45.2
• Pytorch 2.4.1+cu118
• Datasets 3.0.1
• Tokenizers 0.20.1