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wav2vec2-base-checkpoint-5

This model is a fine-tuned version of jiobiala24/wav2vec2-base-checkpoint-4 on the common_voice dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9849
  • Wer: 0.3354

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: 32
  • 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: 1000
  • num_epochs: 30
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.3947 1.96 1000 0.5749 0.3597
0.2856 3.93 2000 0.6212 0.3479
0.221 5.89 3000 0.6280 0.3502
0.1755 7.86 4000 0.6517 0.3526
0.1452 9.82 5000 0.7115 0.3481
0.1256 11.79 6000 0.7687 0.3509
0.1117 13.75 7000 0.7785 0.3490
0.0983 15.72 8000 0.8115 0.3442
0.0877 17.68 9000 0.8290 0.3429
0.0799 19.65 10000 0.8517 0.3412
0.0733 21.61 11000 0.9370 0.3448
0.066 23.58 12000 0.9157 0.3410
0.0623 25.54 13000 0.9673 0.3377
0.0583 27.5 14000 0.9804 0.3348
0.0544 29.47 15000 0.9849 0.3354

Framework versions

  • Transformers 4.11.3
  • Pytorch 1.10.0+cu111
  • Datasets 1.13.3
  • Tokenizers 0.10.3
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Dataset used to train jiobiala24/wav2vec2-base-checkpoint-5