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patrickvonplaten
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xls-r-300-sv-cv7

Automatic Speech Recognition Transformers PyTorch TensorBoard
wav2vec2 generated_from_trainer hf-asr-leaderboard mozilla-foundation/common_voice_7_0 robust-speech-event sv Eval Results Inference Endpoints
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metadata
language:
  - sv-SE
license: apache-2.0
tags:
  - automatic-speech-recognition
  - generated_from_trainer
  - hf-asr-leaderboard
  - mozilla-foundation/common_voice_7_0
  - robust-speech-event
  - sv
datasets:
  - mozilla-foundation/common_voice_7_0
model-index:
  - name: XLS-R-300M - Swedish - CV7 - v2
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 7
          type: mozilla-foundation/common_voice_7_0
          args: sv-SE
        metrics:
          - name: Test WER
            type: wer
            value: 15.99
          - name: Test CER
            type: cer
            value: 5.2
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Robust Speech Event - Dev Data
          type: speech-recognition-community-v2/dev_data
          args: sv
        metrics:
          - name: Test WER
            type: wer
            value: 24.41
          - name: Test CER
            type: cer
            value: 11.88

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

  • Loss: 0.2604
  • Wer: 0.2334

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: 4
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 1
  • total_train_batch_size: 32
  • total_eval_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: 50.0
  • mixed_precision_training: Native AMP

Training results

See Tensorboard

Evaluation Commands

  1. To evaluate on mozilla-foundation/common_voice_7_0 with split test
python eval.py --model_id patrickvonplaten/xls-r-300-sv-cv7 --dataset mozilla-foundation/common_voice_7_0 --config sv-SE --split test
  1. To evaluate on speech-recognition-community-v2/dev_data
python eval.py --model_id patrickvonplaten/xls-r-300-sv-cv7 --dataset speech-recognition-community-v2/dev_data --config sv --split validation --chunk_length_s 5.0 --stride_length_s 1.0

Framework versions

  • Transformers 4.17.0.dev0
  • Pytorch 1.9.0+cu111
  • Datasets 1.18.4.dev0
  • Tokenizers 0.10.3