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whisper_NCHLT_speech_corpus_Zulu_50hr_v1

Automatic Speech Recognition
Transformers
Safetensors
Zulu
whisper
Generated from Trainer
Eval Results
Inference Endpoints
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metadata
library_name: transformers
language:
  - zul
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - NCHLT_speech_corpus
metrics:
  - wer
model-index:
  - name: Whisper Small Shona - Beijuka Bruno
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: NCHLT_speech_corpus/Zulu
          type: NCHLT_speech_corpus
          args: 'config: zul, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 58.977948897444875

Whisper Small Shona - Beijuka Bruno

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

  • Loss: 1.3971
  • Wer: 58.9779
  • Cer: 19.2528

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: 8
  • 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
  • num_epochs: 100

Training results

Training Loss Epoch Step Validation Loss Wer Cer
0.3596 1.0 5045 0.3025 28.6289 4.3976
0.1187 2.0 10090 0.2591 24.1626 3.7419
0.0531 3.0 15135 0.2731 22.8227 3.6080
0.0239 4.0 20180 0.2875 21.5721 3.6466
0.0129 5.0 25225 0.3149 21.9071 3.4945
0.0087 6.0 30270 0.3239 20.5449 3.2903
0.007 7.0 35315 0.3394 20.7459 3.3448
0.0059 8.0 40360 0.3542 19.9866 3.1496
0.0052 9.0 45405 0.3570 20.9692 3.3879
0.0044 10.0 50450 0.3667 20.3886 3.3107
0.0046 11.0 55495 0.3692 20.2099 3.3130
0.0039 12.0 60540 0.3664 20.8352 3.9007
0.0044 13.0 65585 0.3874 20.3662 3.6261
0.0038 14.0 70630 0.3915 20.5672 3.3561
0.0032 15.0 75675 0.3842 20.8352 3.4083
0.0029 16.0 80720 0.4151 20.7459 3.4128
0.0029 17.0 85765 0.4071 20.6789 3.3039
0.0026 18.0 90810 0.4144 20.1653 3.2767

Framework versions

  • Transformers 4.47.0
  • Pytorch 2.1.0+cu118
  • Datasets 3.1.0
  • Tokenizers 0.21.0