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metadata
library_name: transformers
language:
  - mr
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 Marathi - Devesh
    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: 42.89858809876861

Whisper Small Marathi - Devesh

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: 0.4955
  • Wer: 42.8986

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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 5000

Training results

Training Loss Epoch Step Validation Loss Wer
0.0675 4.0650 1000 0.2960 46.0318
0.0052 8.1301 2000 0.3973 43.8399
0.0015 12.1951 3000 0.4573 43.4337
0.0001 16.2602 4000 0.4837 42.9308
0.0001 20.3252 5000 0.4955 42.8986

Framework versions

  • Transformers 4.51.3
  • Pytorch 2.1.0+cu118
  • Datasets 3.5.0
  • Tokenizers 0.21.1