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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: 1.1679
  • Wer: 0.5761

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: 0.000111
  • 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: 300
  • num_epochs: 200
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
8.3852 10.51 200 3.6402 1.0
3.5374 21.05 400 3.3894 1.0
2.8645 31.56 600 1.3143 0.8303
1.1784 42.1 800 0.9417 0.6661
0.7805 52.62 1000 0.9292 0.6237
0.5973 63.15 1200 0.9489 0.6014
0.4784 73.67 1400 0.9916 0.5962
0.4138 84.21 1600 1.0272 0.6121
0.3491 94.72 1800 1.0412 0.5984
0.3062 105.26 2000 1.0769 0.6005
0.2707 115.77 2200 1.0708 0.5752
0.2459 126.31 2400 1.1285 0.6009
0.2234 136.82 2600 1.1209 0.5949
0.2035 147.36 2800 1.1348 0.5842
0.1876 157.87 3000 1.1480 0.5872
0.1669 168.41 3200 1.1496 0.5838
0.1595 178.92 3400 1.1721 0.5778
0.1505 189.46 3600 1.1654 0.5744
0.1486 199.97 3800 1.1679 0.5761

Framework versions

  • Transformers 4.16.1
  • Pytorch 1.10.0+cu111
  • Datasets 1.18.2
  • Tokenizers 0.11.0
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Dataset used to train DrishtiSharma/wav2vec2-large-xls-r-300m-as-with-LM-v2

Evaluation results