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infinitejoy/wav2vec2-large-xls-r-300m-indonesian

🤗 Hugging Face sourceautomatic-speech-recognitionapache-2.043 GBother✓ 2 checksumsupdated today
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wav2vec2-large-xls-r-300m-indonesian

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - ID dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2759
  • Wer: 0.3256

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: 7e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 4000
  • num_epochs: 100.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
3.0387 4.72 1000 3.0892 1.0
1.7911 9.43 2000 0.8451 0.6702
1.2826 14.15 3000 0.4211 0.4166
1.1802 18.87 4000 0.3508 0.4690
1.1065 23.58 5000 0.3319 0.4662
1.0921 28.3 6000 0.3056 0.3880
1.0366 33.02 7000 0.2997 0.3665
0.9988 37.74 8000 0.2972 0.3653
0.9864 42.45 9000 0.2697 0.3371
0.9558 47.17 10000 0.2739 0.3141
0.9094 51.89 11000 0.2657 0.3533
0.9034 56.6 12000 0.2699 0.3397
0.8907 61.32 13000 0.2765 0.3470
0.8631 66.04 14000 0.2774 0.3346
0.8389 70.75 15000 0.2743 0.3365
0.8214 75.47 16000 0.2778 0.3201
0.8195 80.19 17000 0.2725 0.3286
0.7994 84.91 18000 0.2782 0.3315
0.7816 89.62 19000 0.2775 0.3363
0.7816 94.34 20000 0.2731 0.3278
0.7635 99.06 21000 0.2767 0.3259

Framework versions

  • Transformers 4.16.0.dev0
  • Pytorch 1.10.1+cu102
  • Datasets 1.17.1.dev0
  • Tokenizers 0.11.0