xls-r-hausa-40 / README.md
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metadata
language:
  - ha
license: apache-2.0
tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_8_0
  - generated_from_trainer
  - robust-speech-event
  - hf-asr-leaderboard
datasets:
  - mozilla-foundation/common_voice_8_0
model-index:
  - name: ''
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 8.0
          type: mozilla-foundation/common_voice_8_0
          args: ha
        metrics:
          - name: Test WER
            type: wer
            value: 51.31

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - HA dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4998
  • Wer: 0.5153

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: 9.6e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 2000
  • num_epochs: 80.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
3.0021 8.33 500 2.9059 1.0
2.6604 16.66 1000 2.6402 0.9892
1.2216 24.99 1500 0.6051 0.6851
1.0754 33.33 2000 0.5408 0.6464
0.9582 41.66 2500 0.5521 0.5935
0.8653 49.99 3000 0.5156 0.5550
0.7867 58.33 3500 0.5439 0.5606
0.7265 66.66 4000 0.4863 0.5255
0.6699 74.99 4500 0.5050 0.5169

Framework versions

  • Transformers 4.17.0.dev0
  • Pytorch 1.10.2+cu113
  • Datasets 1.18.4.dev0
  • Tokenizers 0.11.0