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wav2vec2_common_voice_accents_3

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

  • Loss: 0.0042

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: 48
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • total_train_batch_size: 384
  • 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: 500
  • num_epochs: 30
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
4.584 1.27 400 1.1439
0.481 2.55 800 0.1986
0.2384 3.82 1200 0.1060
0.1872 5.1 1600 0.1016
0.158 6.37 2000 0.0942
0.1427 7.64 2400 0.0646
0.1306 8.92 2800 0.0612
0.1197 10.19 3200 0.0423
0.1129 11.46 3600 0.0381
0.1054 12.74 4000 0.0326
0.0964 14.01 4400 0.0293
0.0871 15.29 4800 0.0239
0.0816 16.56 5200 0.0168
0.0763 17.83 5600 0.0202
0.0704 19.11 6000 0.0224
0.0669 20.38 6400 0.0208
0.063 21.66 6800 0.0074
0.0585 22.93 7200 0.0126
0.0548 24.2 7600 0.0086
0.0512 25.48 8000 0.0080
0.0487 26.75 8400 0.0052
0.0455 28.03 8800 0.0062
0.0433 29.3 9200 0.0042

Framework versions

  • Transformers 4.17.0
  • Pytorch 1.10.2+cu102
  • Datasets 1.18.4
  • Tokenizers 0.11.6
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Dataset used to train willcai/wav2vec2_common_voice_accents_3