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whisper_DigitalUmuganda_Afrivoice_Shona_10hr_v1

Automatic Speech Recognition
Transformers
Safetensors
sh
whisper
Generated from Trainer
Eval Results
Inference Endpoints
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metadata
library_name: transformers
language:
  - sh
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - DigitalUmuganda/Afrivoice
metrics:
  - wer
model-index:
  - name: Whisper Small Shona - Beijuka Bruno
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Afrivoice_shona
          type: DigitalUmuganda/Afrivoice
          args: 'config: sh, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 43.77763739734681

Whisper Small Shona - Beijuka Bruno

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

  • Loss: 0.9885
  • Wer: 43.7776
  • Cer: 10.5354

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 100

Training results

Training Loss Epoch Step Validation Loss Wer Cer
1.4704 1.0 221 0.8345 57.1641 12.8241
0.588 2.0 442 0.5671 43.1463 9.0338
0.3483 3.0 663 0.4983 39.4835 8.0809
0.2005 4.0 884 0.4918 38.3288 8.0162
0.1084 5.0 1105 0.5136 38.5771 7.9115
0.0554 6.0 1326 0.5454 38.4405 8.3641
0.0285 7.0 1547 0.5648 38.9744 8.2256
0.0182 8.0 1768 0.5721 38.2915 7.7560
0.012 9.0 1989 0.6069 36.6153 7.7960
0.008 10.0 2210 0.6072 37.8445 7.8022
0.0059 11.0 2431 0.6271 36.4167 7.2819
0.0038 12.0 2652 0.6236 37.1244 7.9361
0.0039 13.0 2873 0.6414 37.1244 7.3650
0.0034 14.0 3094 0.6356 36.3546 7.2603
0.003 15.0 3315 0.6491 36.5284 7.4512
0.0049 16.0 3536 0.6539 38.2915 9.1293
0.0058 17.0 3757 0.6732 38.7758 7.7114
0.0049 18.0 3978 0.6704 37.4224 7.5236
0.0046 19.0 4199 0.6662 37.3231 7.7945
0.0028 20.0 4420 0.6718 36.3422 7.5328
0.002 21.0 4641 0.6796 36.4912 7.5821
0.0019 22.0 4862 0.6730 36.0318 7.5528
0.0021 23.0 5083 0.6833 37.0002 7.6914
0.0018 24.0 5304 0.6928 36.3919 7.4358
0.0018 25.0 5525 0.7052 35.4358 7.4728
0.0014 26.0 5746 0.7111 36.5533 8.0793
0.0019 27.0 5967 0.6961 35.9945 7.2634
0.002 28.0 6188 0.7029 35.6345 7.2942
0.0016 29.0 6409 0.7191 35.7090 7.2649
0.002 30.0 6630 0.7013 35.6593 7.2249
0.0016 31.0 6851 0.7105 35.8704 7.5975
0.0023 32.0 7072 0.7251 35.4482 7.3065
0.0017 33.0 7293 0.7093 35.4482 7.3203
0.0017 34.0 7514 0.7264 36.2180 7.5112
0.0018 35.0 7735 0.7227 35.4731 7.4450

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.1.0+cu118
  • Datasets 3.0.0
  • Tokenizers 0.19.1