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whisper-medium-nepali

Automatic Speech Recognition
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metadata
library_name: transformers
language:
  - ne
license: apache-2.0
base_model: openai/whisper-medium
tags:
  - generated_from_trainer
datasets:
  - kiranpantha/OpenSLR54-Whisper
metrics:
  - wer
model-index:
  - name: Whisper Medium Nepali - Kiran Pantha
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: OpenSLR54
          type: kiranpantha/OpenSLR54-Whisper
          config: default
          split: test
          args: 'config: ne, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 21.99074074074074

Whisper Medium Nepali - Kiran Pantha

This model is a fine-tuned version of openai/whisper-medium on the OpenSLR54 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1608
  • Wer: 21.9907
  • Cer: 5.3068

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
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Cer Validation Loss Wer
0.2877 0.3597 300 13.1055 0.2588 48.6574
0.1865 0.7194 600 10.0741 0.2052 39.9537
0.1155 1.0791 900 8.1217 0.1633 31.8981
0.0992 1.4388 1200 7.6923 0.1577 30.6250
0.094 1.7986 1500 7.1969 0.1418 28.3796
0.0454 2.1583 1800 6.7308 0.1472 26.6898
0.0333 2.5180 2100 6.6353 0.1512 27.0602
0.0446 2.8777 2400 6.25 0.1409 25.5556
0.0204 3.2374 2700 6.5399 0.1513 25.8796
0.016 3.5971 3000 5.9674 0.1560 24.8380
0.0166 3.9568 3300 6.0592 0.1573 25.0926
0.0052 4.3165 3600 5.7802 0.1566 23.3796
0.0068 4.6763 3900 5.5233 0.1544 22.7083
0.0013 5.0360 4200 5.4756 0.1568 22.7546
0.001 5.3957 4500 0.1606 22.0139 5.3178
0.0017 5.7554 4800 0.1608 21.9907 5.3068

Framework versions

  • Transformers 4.46.3
  • Pytorch 2.5.1+cxx11.abi
  • Datasets 3.2.0
  • Tokenizers 0.20.3