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This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_9_0 - UR dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4147
  • Wer: 0.3172
  • Cer: 0.1050

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: 7.5e-05
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • training_steps: 5108
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
3.2894 7.83 400 3.1501 1.0 1.0
1.8586 15.68 800 0.8871 0.6721 0.2402
1.3431 23.52 1200 0.5813 0.5502 0.1939
1.2052 31.37 1600 0.4956 0.4788 0.1665
1.1097 39.21 2000 0.4447 0.4143 0.1397
1.0528 47.06 2400 0.4439 0.3961 0.1333
0.9939 54.89 2800 0.4348 0.4014 0.1379
0.9441 62.74 3200 0.4236 0.3653 0.1223
0.913 70.58 3600 0.4309 0.3475 0.1157
0.8678 78.43 4000 0.4270 0.3337 0.1110
0.8414 86.27 4400 0.4158 0.3220 0.1070
0.817 94.12 4800 0.4185 0.3231 0.1072

Framework versions

  • Transformers 4.19.0.dev0
  • Pytorch 1.11.0+cu102
  • Datasets 2.1.1.dev0
  • Tokenizers 0.12.1
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Dataset used to train anuragshas/wav2vec2-xls-r-300m-ur-cv9-with-lm

Evaluation results