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Model description

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - JA dataset.

Benchmark WER result:

COMMON VOICE 7.0 COMMON VOICE 8.0
without LM 15.74 25.10
with 4-grams LM 15.37 16.09

Benchmark CER result:

COMMON VOICE 7.0 COMMON VOICE 8.0
without LM 9.51 9.95
with 4-grams LM 6.91 7.15

Evaluation

Please use the eval.py file to run the evaluation:

python eval.py --model_id vutankiet2901/wav2vec2-large-xlsr-53-ja --dataset mozilla-foundation/common_voice_7_0 --config ja --split test --log_outputs

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0003
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • 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: 50.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
4.7776 4.73 1500 2.9540 0.9772 0.8489
1.9076 9.46 3000 0.7146 0.5371 0.2484
1.507 14.2 4500 0.5843 0.4689 0.2196
1.3742 18.93 6000 0.5286 0.4321 0.1988
1.2776 23.66 7500 0.5007 0.4056 0.1870
1.2003 28.39 9000 0.4676 0.3848 0.1802
1.1281 33.12 10500 0.4524 0.3694 0.1720
1.0657 37.85 12000 0.4449 0.3590 0.1681
1.0129 42.59 13500 0.4266 0.3423 0.1617
0.9691 47.32 15000 0.4214 0.3375 0.1587

Framework versions

  • Transformers 4.16.0.dev0
  • Pytorch 1.10.1+cu102
  • Datasets 1.18.3
  • Tokenizers 0.11.0
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Dataset used to train vutankiet2901/wav2vec2-large-xlsr-53-ja

Evaluation results