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Model description

This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - JA

Benchmark WER result:

COMMON VOICE 7.0 COMMON VOICE 8.0
without LM 16.97 17.95
with 4-grams LM 11.77 12.23

Benchmark CER result:

COMMON VOICE 7.0 COMMON VOICE 8.0
without LM 6.82 7.05
with 4-grams LM 5.22 5.33

Evaluation

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

pip install mecab-python3 unidic-lite pykakasi
python eval.py --model_id vutankiet2901/wav2vec2-xls-r-1b-ja --dataset mozilla-foundation/common_voice_8_0 --config ja --split test --log_outputs

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 2000
  • num_epochs: 100.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
3.484 9.49 1500 1.1849 0.7543 0.4099
1.3582 18.98 3000 0.4320 0.3489 0.1591
1.1716 28.48 4500 0.3835 0.3175 0.1454
1.0951 37.97 6000 0.3732 0.3033 0.1405
1.04 47.47 7500 0.3485 0.2898 0.1360
0.9768 56.96 9000 0.3386 0.2787 0.1309
0.9129 66.45 10500 0.3363 0.2711 0.1272
0.8614 75.94 12000 0.3386 0.2676 0.1260
0.8092 85.44 13500 0.3356 0.2610 0.1240
0.7658 94.93 15000 0.3316 0.2564 0.1218

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-xls-r-1b-ja

Evaluation results