whisper_hf / README.md
whispy's picture
Update README.md
5a85972
|
raw
history blame
2.08 kB
metadata
language:
  - it
license: apache-2.0
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Small Italian
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          args: 'config: it, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 17.391605006569392

Whisper Small Italian

This model is a fine-tuned version of openai/whisper-base on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1185
  • Wer: 17.3916

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
  • gradient_accumulation_steps: 1
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 954
  • mixed_precision_training: Native AMP

Training results

Training Loss Step Validation Loss Wer
1.4744 100 1.1852 117.6059
0.7241 200 0.7452 79.7386
0.3321 300 0.3215 21.0497
0.2930 400 0.3030 20.2129
0.2698 500 0.2982 19.7635
0.2453 600 0.2898 19.0097
0.2338 700 0.2768 18.7054
0.2402 800 0.2646 18.2214
0.2340 900 0.2581 17.3916

Framework versions

  • Transformers 4.25.0.dev0
  • Pytorch 1.12.1+cu113
  • Datasets 2.7.1
  • Tokenizers 0.13.2