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metadata
library_name: transformers
language:
  - sn
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
  - generated_from_trainer
datasets:
  - DigitalUmuganda_Afrivoice/Shona
metrics:
  - wer
model-index:
  - name: facebook/mms-1b-all
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: DigitalUmuganda
          type: DigitalUmuganda_Afrivoice/Shona
        metrics:
          - name: Wer
            type: wer
            value: 0.28446474561446133

facebook/mms-1b-all

This model is a fine-tuned version of facebook/mms-1b-all on the DigitalUmuganda dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2197
  • Model Preparation Time: 0.011
  • Wer: 0.2845
  • Cer: 0.0508

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: 0.0003
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • 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: 100
  • num_epochs: 150
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Model Preparation Time Wer Cer
57.4573 0.9818 27 11.9211 0.011 1.8495 2.2226
32.7495 1.9727 54 3.8209 0.011 1.0 0.9976
11.1389 2.9636 81 1.5552 0.011 0.9324 0.3299
2.4363 3.9909 109 0.2450 0.011 0.3251 0.0558
1.0951 4.9818 136 0.2150 0.011 0.3210 0.0535
1.0093 5.9727 163 0.2058 0.011 0.3108 0.0515
0.9759 6.9636 190 0.2019 0.011 0.3125 0.0516
0.9196 7.9909 218 0.1983 0.011 0.3074 0.0509
0.9158 8.9818 245 0.1957 0.011 0.3118 0.0509
0.9027 9.9727 272 0.1943 0.011 0.3142 0.0506
0.8848 10.9636 299 0.1929 0.011 0.3042 0.0498
0.8314 11.9909 327 0.1939 0.011 0.2977 0.0491
0.85 12.9818 354 0.1906 0.011 0.3033 0.0496
0.8357 13.9727 381 0.1914 0.011 0.3013 0.0486
0.8153 14.9636 408 0.1901 0.011 0.2972 0.0482
0.7754 15.9909 436 0.1918 0.011 0.2996 0.0489
0.7957 16.9818 463 0.1894 0.011 0.3071 0.0490
0.7801 17.9727 490 0.1887 0.011 0.2955 0.0478
0.7703 18.9636 517 0.1904 0.011 0.3008 0.0481
0.7231 19.9909 545 0.1904 0.011 0.2994 0.0486
0.7414 20.9818 572 0.1883 0.011 0.2974 0.0480
0.7336 21.9727 599 0.1885 0.011 0.2889 0.0474
0.7154 22.9636 626 0.1887 0.011 0.2909 0.0473
0.6867 23.9909 654 0.1876 0.011 0.2904 0.0473
0.7064 24.9818 681 0.1880 0.011 0.2916 0.0474
0.6896 25.9727 708 0.1894 0.011 0.2943 0.0473
0.68 26.9636 735 0.1896 0.011 0.3057 0.0476
0.6438 27.9909 763 0.1893 0.011 0.3011 0.0478
0.658 28.9818 790 0.1901 0.011 0.2940 0.0472
0.6452 29.9727 817 0.1910 0.011 0.2962 0.0476
0.6396 30.9636 844 0.1914 0.011 0.2896 0.0473
0.6067 31.9909 872 0.1941 0.011 0.2894 0.0473

Framework versions

  • Transformers 4.47.0.dev0
  • Pytorch 2.1.0+cu118
  • Datasets 3.0.2
  • Tokenizers 0.20.1