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wav2vec2-xlsr-53-rm-vallader-with-lm

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

  • Loss: 0.4552
  • Wer: 0.3206

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: 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_ratio: 0.112
  • num_epochs: 30

Training results

Training Loss Epoch Step Validation Loss Wer
0.2379 3.12 100 0.4041 0.3396
0.103 6.25 200 0.4400 0.3337
0.0664 9.38 300 0.4239 0.3315
0.0578 12.5 400 0.4303 0.3267
0.0446 15.62 500 0.4575 0.3274
0.041 18.75 600 0.4451 0.3223
0.0402 21.88 700 0.4507 0.3206
0.0374 25.0 800 0.4649 0.3208
0.0371 28.12 900 0.4552 0.3206

Framework versions

  • Transformers 4.15.0
  • Pytorch 1.10.0+cu111
  • Datasets 1.18.1
  • Tokenizers 0.10.3
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Dataset used to train anuragshas/wav2vec2-xlsr-53-rm-vallader-with-lm