wav2vec2-E30_freq_pause

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

  • Loss: 4.2019
  • Cer: 75.5110

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: 0.0001
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 50
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Cer
35.7962 0.1289 200 6.9049 100.0
14.8713 0.2579 400 4.9998 90.5193
10.3032 0.3868 600 4.5702 93.8440
8.67 0.5158 800 4.6552 92.9570
5.3475 0.6447 1000 4.5889 94.0437
4.9653 0.7737 1200 4.6626 93.9203
5.4367 0.9026 1400 4.4921 93.8322
5.1023 1.0316 1600 4.5898 93.5620
4.6675 1.1605 1800 4.3543 93.2801
4.9955 1.2895 2000 4.3195 92.9159
4.7843 1.4184 2200 4.2888 92.4871
4.7112 1.5474 2400 4.2545 92.2580
4.958 1.6763 2600 4.3499 85.8141
4.5195 1.8053 2800 4.2328 83.8522
4.7397 1.9342 3000 4.2644 82.5540
4.2707 2.0632 3200 4.3350 83.0298
4.6255 2.1921 3400 4.1961 81.6671
4.2181 2.3211 3600 4.1846 79.9107
4.6953 2.4500 3800 4.3664 74.8590
4.2375 2.5790 4000 4.5549 74.7650
4.186 2.7079 4200 4.2655 75.3818
4.2477 2.8369 4400 4.1909 76.5625
4.2201 2.9658 4600 4.2019 75.5110

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.19.1
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