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Khalsuu/english-filipino-wav2vec2-l-xls-r-test-04

🤗 Hugging Face 来源automatic-speech-recognitionapache-2.03.8 GBother✓ 4 个校验和今天更新
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english-filipino-wav2vec2-l-xls-r-test-04

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

  • Loss: 1.0713
  • Wer: 0.5078

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: 0.002
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 40
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
2.2131 2.09 400 0.7100 0.6832
0.6539 4.19 800 0.8307 0.6602
0.5081 6.28 1200 0.7120 0.6297
0.42 8.38 1600 0.7309 0.6299
0.3482 10.47 2000 0.7665 0.6148
0.293 12.57 2400 0.7091 0.5840
0.265 14.66 2800 0.8170 0.6102
0.2294 16.75 3200 0.9715 0.6216
0.1872 18.85 3600 0.8516 0.5837
0.1644 20.94 4000 0.8408 0.5767
0.1495 23.04 4400 0.9188 0.5717
0.1276 25.13 4800 1.0149 0.5451
0.116 27.23 5200 1.0220 0.5683
0.1017 29.32 5600 0.9319 0.5253
0.0899 31.41 6000 0.9949 0.5435
0.0861 33.51 6400 1.1029 0.5467
0.0766 35.6 6800 1.0219 0.5193
0.065 37.7 7200 1.0836 0.5214
0.0588 39.79 7600 1.0713 0.5078

Framework versions

  • Transformers 4.11.3
  • Pytorch 1.10.0+cu113
  • Datasets 1.18.3
  • Tokenizers 0.10.3