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wav2vec2-large-xlsr-53-th-main

This model is a fine-tuned version of airesearch/wav2vec2-large-xlsr-53-th on the common_voice dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1340
  • Wer: 0.4686

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: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 30
  • num_epochs: 40
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
5.2524 3.23 100 3.3222 1.0
3.2913 6.45 200 3.1818 1.0
2.222 9.68 300 1.2497 0.5335
1.1558 12.9 400 1.0792 0.5214
0.934 16.13 500 1.0663 0.4986
0.8023 19.35 600 1.0331 0.4893
0.7041 22.58 700 1.0801 0.4800
0.6576 25.81 800 1.1123 0.4886
0.6061 29.03 900 1.0748 0.4829
0.5649 32.26 1000 1.1187 0.4679
0.5717 35.48 1100 1.1267 0.4715
0.5267 38.71 1200 1.1340 0.4686

Framework versions

  • Transformers 4.28.0
  • Pytorch 2.0.1+cu118
  • Datasets 1.16.1
  • Tokenizers 0.13.3
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Dataset used to train BALAKA/wav2vec2-large-xlsr-53-th-swear-words

Space using BALAKA/wav2vec2-large-xlsr-53-th-swear-words 1

Evaluation results