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wav2vec2-large-xlsr-sw_ndizi_782_100_epochs

This model is a fine-tuned version of smutuvi/wav2vec2-large-xlsr-sw on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 3.1009
  • Wer: 0.4847

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: 4
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 8
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 100
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.4035 4.79 400 1.2492 0.5608
0.8489 9.58 800 1.0208 0.5114
0.632 14.37 1200 1.3292 0.5306
0.4653 19.16 1600 1.5159 0.5109
0.3598 23.95 2000 1.4650 0.5450
0.2776 28.74 2400 1.8568 0.5124
0.218 33.53 2800 2.0913 0.5188
0.1711 38.32 3200 2.2706 0.5035
0.141 43.11 3600 2.3050 0.5094
0.1162 47.9 4000 2.4539 0.5025
0.1007 52.69 4400 2.4754 0.5020
0.0881 57.49 4800 2.5512 0.5030
0.0816 62.28 5200 2.6458 0.5064
0.0792 67.07 5600 2.7869 0.5025
0.06 71.86 6000 2.9063 0.5040
0.0594 76.65 6400 2.8363 0.5049
0.0527 81.44 6800 3.0801 0.4921
0.0473 86.23 7200 3.0959 0.4867
0.0471 91.02 7600 3.0942 0.4852
0.0405 95.81 8000 3.1009 0.4847

Framework versions

  • Transformers 4.37.1
  • Pytorch 2.2.1+cu118
  • Datasets 2.16.1
  • Tokenizers 0.15.0
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