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metadata
language:
  - or
license: apache-2.0
tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_9_0
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_9_0
metrics:
  - wer
model-index:
  - name: XLS-R-300M - Odia
    results:
      - task:
          type: automatic-speech-recognition
          name: Speech Recognition
        dataset:
          type: mozilla-foundation/common_voice_9_0
          name: Common Voice 9
          args: or
        metrics:
          - type: wer
            value: 44.343
            name: Test WER
          - name: Test CER
            type: cer
            value: 10.989

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_9_0 - OR dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7886
  • Wer: 0.5495
  • Cer: 0.1311

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: 7.5e-05
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • training_steps: 3071
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
3.5875 66.62 400 3.4289 1.0 1.0
1.4065 133.31 800 0.7243 0.6619 0.1734
1.007 199.92 1200 0.6611 0.5831 0.1457
0.7984 266.62 1600 0.6387 0.5520 0.1332
0.6117 333.31 2000 0.7424 0.5682 0.1376
0.4926 399.92 2400 0.7627 0.5514 0.1314
0.416 466.62 2800 0.7816 0.5604 0.1320

Framework versions

  • Transformers 4.19.0.dev0
  • Pytorch 1.11.0+cu102
  • Datasets 2.1.1.dev0
  • Tokenizers 0.12.1