community-events / README.md
showgan's picture
End of training
3f7bb26 verified
metadata
language:
  - hi
license: apache-2.0
base_model: openai/whisper-small
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Small Hi - Sanchit Gandhi
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          config: hi
          split: None
          args: hi
        metrics:
          - name: Wer
            type: wer
            value: 18.063821994322865

Whisper Small Hi - Sanchit Gandhi

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

  • Loss: 0.5714
  • Wer: 18.0638

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: 8
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0067 9.78 1000 0.4138 18.9383
0.0008 19.56 2000 0.4948 18.4736
0.0001 29.34 3000 0.5353 18.0730
0.0001 39.12 4000 0.5624 18.0570
0.0 48.9 5000 0.5714 18.0638

Framework versions

  • Transformers 4.40.0.dev0
  • Pytorch 2.2.2+cu121
  • Datasets 2.18.1.dev0
  • Tokenizers 0.15.2