xls-r-300m-fr / README.md
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add results for train and test
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metadata
language:
  - fr
license: apache-2.0
tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_7_0
  - generated_from_trainer
  - robust-speech-event
model-index:
  - name: XLS-R-300M - French
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 7
          type: mozilla-foundation/common_voice_7_0
          args: fr
        metrics:
          - name: Test WER
            type: wer
            value: 24.56
          - name: Test CER
            type: cer
            value: 7.3

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - FR dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2619
  • Wer: 0.2457

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: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 2000
  • num_epochs: 2.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
3.495 0.16 500 3.3883 1.0
2.9095 0.32 1000 2.9152 1.0000
1.8434 0.49 1500 1.0473 0.7446
1.4298 0.65 2000 0.5729 0.5130
1.1937 0.81 2500 0.3795 0.3450
1.1248 0.97 3000 0.3321 0.3052
1.0835 1.13 3500 0.3038 0.2805
1.0479 1.3 4000 0.2910 0.2689
1.0413 1.46 4500 0.2798 0.2593
1.014 1.62 5000 0.2727 0.2512
1.004 1.78 5500 0.2646 0.2471
0.9949 1.94 6000 0.2619 0.2457

Eval results on Common Voice 7 "test" (WER):

Without LM With LM
24.56 To be computed

Framework versions

  • Transformers 4.17.0.dev0
  • Pytorch 1.10.2+cu102
  • Datasets 1.18.2.dev0
  • Tokenizers 0.11.0