wav2vec2-large-xlsr-53-demo-colab

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the common_voice dataset. It achieves the following results on the evaluation set:

  • Loss: 6.7860
  • Wer: 1.1067

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: 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: 500
  • num_epochs: 1000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
8.2273 44.42 400 3.3544 1.0
0.9228 88.84 800 4.7054 1.1601
0.1423 133.32 1200 5.9489 1.1578
0.0751 177.74 1600 5.5939 1.1717
0.0554 222.21 2000 6.1230 1.1717
0.0356 266.63 2400 6.2845 1.1613
0.0288 311.11 2800 6.6109 1.2100
0.0223 355.53 3200 6.5605 1.1299
0.0197 399.95 3600 7.1242 1.1682
0.0171 444.42 4000 7.2452 1.1578
0.0149 488.84 4400 7.4048 1.0684
0.0118 533.32 4800 6.6227 1.1172
0.011 577.74 5200 6.7909 1.1566
0.0095 622.21 5600 6.8088 1.1102
0.0077 666.63 6000 7.4451 1.1311
0.0062 711.11 6400 6.8486 1.0777
0.0051 755.53 6800 6.8812 1.1241
0.0051 799.95 7200 6.9987 1.1450
0.0041 844.42 7600 7.3048 1.1323
0.0044 888.84 8000 6.6644 1.1125
0.0031 933.32 8400 6.6298 1.1148
0.0027 977.74 8800 6.7860 1.1067

Framework versions

  • Transformers 4.11.3
  • Pytorch 1.10.0+cu111
  • Datasets 1.14.0
  • Tokenizers 0.10.3
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Dataset used to train rafiulrumy/wav2vec2-large-xlsr-53-demo-colab

Evaluation results