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wav2vec2-large-xlsr-53-W2V2-TR-MED

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

  • Loss: 0.4467
  • Wer: 0.4598

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: 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: 500
  • num_epochs: 60
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
5.1343 4.21 400 2.3674 1.0372
0.8075 8.42 800 0.4583 0.6308
0.3209 12.63 1200 0.4291 0.5531
0.2273 16.84 1600 0.4348 0.5378
0.1764 21.05 2000 0.4550 0.5326
0.148 25.26 2400 0.4839 0.5319
0.1268 29.47 2800 0.4515 0.5070
0.1113 33.68 3200 0.4590 0.4930
0.1025 37.89 3600 0.4546 0.4888
0.0922 42.11 4000 0.4782 0.4852
0.082 46.32 4400 0.4605 0.4752
0.0751 50.53 4800 0.4358 0.4689
0.0699 54.74 5200 0.4359 0.4629
0.0633 58.95 5600 0.4467 0.4598

Framework versions

  • Transformers 4.11.3
  • Pytorch 1.10.0+cu111
  • Datasets 1.14.0
  • Tokenizers 0.10.3
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Dataset used to train emre/wav2vec2-large-xlsr-53-W2V2-TR-MED