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Malasar_Luke

Automatic Speech Recognition
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PyTorch
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Malasar
whisper
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Malasar_Luke / README.md
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metadata
language:
  - ymr
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: kavyamanohar/Malasar_Luke
    results: []

kavyamanohar/Malasar_Luke

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

  • Loss: 0.6056
  • Wer: 58.9377

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: 32
  • eval_batch_size: 16
  • 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: 2000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.1635 11.36 250 0.3183 63.2210
0.0134 22.73 500 0.4616 63.7350
0.0023 34.09 750 0.5199 59.6802
0.0004 45.45 1000 0.5627 58.5951
0.0003 56.82 1250 0.5831 59.0520
0.0002 68.18 1500 0.5959 58.9949
0.0002 79.55 1750 0.6032 59.1091
0.0002 90.91 2000 0.6056 58.9377

Framework versions

  • Transformers 4.37.0.dev0
  • Pytorch 2.0.1+cu117
  • Datasets 2.12.0
  • Tokenizers 0.15.0