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wav2vec2-large-xls-r-300m-ar

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: 0.4819
  • Wer: 0.4244

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: 3e-05
  • train_batch_size: 32
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 2
  • 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: 400
  • num_epochs: 30
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
11.0435 0.67 400 4.3104 1.0
3.4451 1.34 800 3.1566 1.0
3.1399 2.01 1200 3.0532 0.9990
2.8538 2.68 1600 1.6994 0.9238
1.7195 3.35 2000 0.8867 0.6727
1.326 4.02 2400 0.6603 0.5834
1.1561 4.69 2800 0.5809 0.5479
1.0764 5.36 3200 0.5943 0.5495
1.0144 6.03 3600 0.5344 0.5251
0.965 6.7 4000 0.4844 0.4936
0.927 7.37 4400 0.5048 0.5019
0.8985 8.04 4800 0.5809 0.5267
0.8684 8.71 5200 0.4740 0.4753
0.8581 9.38 5600 0.4813 0.4834
0.8334 10.05 6000 0.4515 0.4545
0.8134 10.72 6400 0.4370 0.4543
0.8002 11.39 6800 0.4225 0.4384
0.7884 12.06 7200 0.4593 0.4565
0.7675 12.73 7600 0.4752 0.4680
0.7607 13.4 8000 0.4950 0.4771
0.7475 14.07 8400 0.4373 0.4391
0.7397 14.74 8800 0.4506 0.4541
0.7289 15.41 9200 0.4840 0.4691
0.722 16.08 9600 0.4701 0.4571
0.7067 16.75 10000 0.4561 0.4461
0.7033 17.42 10400 0.4384 0.4347
0.6915 18.09 10800 0.4424 0.4290
0.6854 18.76 11200 0.4635 0.4360
0.6813 19.43 11600 0.4280 0.4147
0.6776 20.1 12000 0.4610 0.4344
0.67 20.77 12400 0.4540 0.4367
0.6653 21.44 12800 0.4509 0.4234
0.6609 22.11 13200 0.4874 0.4444
0.6541 22.78 13600 0.4542 0.4230
0.6528 23.45 14000 0.4732 0.4373
0.6463 24.12 14400 0.4483 0.4188
0.6399 24.79 14800 0.4731 0.4341
0.6353 25.46 15200 0.5031 0.4412
0.6358 26.13 15600 0.4986 0.4397
0.6317 26.8 16000 0.5000 0.4360
0.6262 27.47 16400 0.4958 0.4318
0.6317 28.14 16800 0.4738 0.4234
0.6205 28.81 17200 0.4853 0.4262
0.6205 29.48 17600 0.4819 0.4244

Framework versions

  • Transformers 4.17.0.dev0
  • Pytorch 1.10.2+cu102
  • Datasets 1.18.3
  • Tokenizers 0.11.0
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Dataset used to train ayameRushia/wav2vec2-large-xls-r-300m-ar