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wav2vec2-base-checkpoint-6

This model is a fine-tuned version of jiobiala24/wav2vec2-base-checkpoint-5 on the common_voice dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9738
  • Wer: 0.3323

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
0.3435 1.82 1000 0.5637 0.3419
0.2599 3.65 2000 0.5804 0.3473
0.2043 5.47 3000 0.6481 0.3474
0.1651 7.3 4000 0.6937 0.3452
0.1376 9.12 5000 0.7221 0.3429
0.118 10.95 6000 0.7634 0.3441
0.105 12.77 7000 0.7789 0.3444
0.0925 14.6 8000 0.8209 0.3444
0.0863 16.42 9000 0.8293 0.3440
0.0756 18.25 10000 0.8553 0.3412
0.0718 20.07 11000 0.9006 0.3430
0.0654 21.9 12000 0.9541 0.3458
0.0605 23.72 13000 0.9400 0.3350
0.0552 25.55 14000 0.9547 0.3363
0.0543 27.37 15000 0.9715 0.3348
0.0493 29.2 16000 0.9738 0.3323

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-6