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whisper_DigitalUmuganda_Afrivoice_Shona_5hr_v1

Automatic Speech Recognition
Transformers
Safetensors
sh
whisper
Generated from Trainer
Eval Results
Inference Endpoints
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whisper_DigitalUmuganda_Afrivoice_Shona_5hr_v1 / README.md
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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: 48.36969726420137

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: 1.0076
  • Wer: 48.3697
  • Cer: 11.1051

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
1.9327 1.0 110 1.2601 74.2137 18.0635
0.96 2.0 220 0.7862 54.7179 11.5259
0.5827 3.0 330 0.6185 47.9531 11.3006
0.3706 4.0 440 0.5590 40.7639 8.3464
0.2221 5.0 550 0.5628 40.1897 8.2400
0.1173 6.0 660 0.5671 42.4114 10.2366
0.06 7.0 770 0.5760 40.6141 10.4056
0.033 8.0 880 0.6091 37.2941 7.6798
0.0194 9.0 990 0.6050 36.9945 7.6016
0.0127 10.0 1100 0.6379 36.8198 7.7549
0.0081 11.0 1210 0.6320 36.7449 7.5014
0.0069 12.0 1320 0.6457 36.7948 7.3950
0.0048 13.0 1430 0.6605 37.1193 7.5484
0.0043 14.0 1540 0.6602 36.5701 7.7925
0.0027 15.0 1650 0.6601 36.1957 7.6391
0.0019 16.0 1760 0.6659 35.3220 7.1321
0.0017 17.0 1870 0.6741 35.8213 7.2667
0.0023 18.0 1980 0.6773 36.6201 8.1492
0.0018 19.0 2090 0.6804 35.5966 7.1759
0.0037 20.0 2200 0.6929 35.5467 7.3011
0.0035 21.0 2310 0.6816 36.1208 7.3762
0.0028 22.0 2420 0.6940 35.5716 7.2198
0.0017 23.0 2530 0.6873 35.9710 7.2980
0.0023 24.0 2640 0.7152 36.1208 7.3387
0.004 25.0 2750 0.6968 35.7963 7.3575
0.0032 26.0 2860 0.7012 37.3190 7.5984

Framework versions

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