README.md

metadata

language:
  - ru
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_17_0
metrics:
  - wer
model-index:
  - name: Whisper Small new-ru- AIIA
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 17
          type: mozilla-foundation/common_voice_17_0
          config: ru
          split: test
          args: ru
        metrics:
          - name: Wer
            type: wer
            value: 15.95373835589288

Whisper Small new-ru- AIIA

This model is a fine-tuned version of openai/whisper-small on the Common Voice 17 dataset. It achieves the following results on the evaluation set:

• Loss: 0.2322
• Wer Ortho: 20.5050
• Wer: 15.9537

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: 3e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: constant_with_warmup
• lr_scheduler_warmup_steps: 70
• training_steps: 1000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.3214	0.4371	500	0.2550	21.4272	16.9669
0.2033	0.8741	1000	0.2322	20.5050	15.9537

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.1+cpu
• Datasets 2.20.0
• Tokenizers 0.19.1