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wav2vec2-base-checkpoint-8

This model is a fine-tuned version of jiobiala24/wav2vec2-base-checkpoint-7.1 on the common_voice dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9561
  • Wer: 0.3271

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
0.3117 1.59 1000 0.5514 0.3451
0.2509 3.19 2000 0.5912 0.3328
0.1918 4.78 3000 0.6103 0.3346
0.1612 6.38 4000 0.6469 0.3377
0.1388 7.97 5000 0.6597 0.3391
0.121 9.57 6000 0.6911 0.3472
0.1096 11.16 7000 0.7300 0.3457
0.0959 12.76 8000 0.7660 0.3400
0.0882 14.35 9000 0.8316 0.3394
0.0816 15.95 10000 0.8042 0.3357
0.0739 17.54 11000 0.8087 0.3346
0.0717 19.14 12000 0.8590 0.3353
0.066 20.73 13000 0.8750 0.3336
0.0629 22.33 14000 0.8759 0.3333
0.0568 23.92 15000 0.8963 0.3321
0.0535 25.52 16000 0.9391 0.3323
0.0509 27.11 17000 0.9279 0.3296
0.0498 28.71 18000 0.9561 0.3271

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-8