metadata

language:
  - ml
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: Whisper Small ML - Bharat Ramanathan
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: mozilla-foundation/common_voice_11_0
          type: mozilla-foundation/common_voice_11_0
          config: ml
          split: test
        metrics:
          - type: wer
            value: 25.8
            name: WER
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: google/fleurs
          type: google/fleurs
          config: ml_in
          split: test
        metrics:
          - type: wer
            value: 48.16
            name: WER

Whisper Small ML - Bharat Ramanathan

This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.2308
Wer: 36.7397

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: 64
eval_batch_size: 32
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: 3000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1275	4.03	500	0.1630	35.4015
0.09	9.02	1000	0.1821	40.0243
0.062	14.01	1500	0.2004	37.7129
0.0441	19.0	2000	0.2105	36.2530
0.0335	23.03	2500	0.2250	37.7129
0.0276	28.02	3000	0.2308	36.7397

Framework versions

Transformers 4.26.0.dev0
Pytorch 1.13.0+cu117
Datasets 2.7.1.dev0
Tokenizers 0.13.2