metadata

language:
  - mar
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Small Mar - Harpreet Singh Anand
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          config: mr
          split: None
          args: 'config: mr, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 43.362774804977114

Whisper Small Mar - Harpreet Singh Anand

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: 0.4596
Wer: 43.3628

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
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0658	4.07	1000	0.2928	46.3542
0.004	8.13	2000	0.3973	44.7295
0.0004	12.2	3000	0.4406	43.5046
0.0002	16.26	4000	0.4596	43.3628

Framework versions

Transformers 4.39.2
Pytorch 2.1.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2