whisper-small-np / README.md
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metadata
library_name: transformers
language:
  - ne
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - openslr/openslr
metrics:
  - wer
model-index:
  - name: Whisper Large Nepali - Kiran Pantha
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: OpenSLR54
          type: openslr/openslr
          config: default
          split: test
          args: 'config: ne, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 30.25462962962963

Whisper Large Nepali - Kiran Pantha

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

  • Loss: 0.2112
  • Wer: 30.2546

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: 100
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.2615 0.5995 500 0.2454 47.2685
0.123 1.1990 1000 0.1994 39.3287
0.1145 1.7986 1500 0.1835 36.1574
0.0547 2.3981 2000 0.1813 33.7037
0.0506 2.9976 2500 0.1730 32.2454
0.0204 3.5971 3000 0.1911 32.2454
0.0079 4.1966 3500 0.2009 31.6667
0.0061 4.7962 4000 0.2022 30.0926
0.0022 5.3957 4500 0.2097 30.2546
0.0022 5.9952 5000 0.2112 30.2546

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1