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xls-r-uyghur-cv11

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_11_0 - UG dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2191
  • Wer: 0.3257

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: 16
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 2000
  • num_epochs: 100.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
3.3958 4.36 500 3.3137 1.0
3.032 8.71 1000 2.8586 0.9993
1.3977 13.07 1500 0.4786 0.6375
1.2751 17.43 2000 0.3816 0.5393
1.2113 21.79 2500 0.3451 0.5099
1.156 26.14 3000 0.3245 0.4919
1.1226 30.5 3500 0.2992 0.4441
1.0913 34.86 4000 0.2831 0.4315
1.0615 39.22 4500 0.2808 0.4340
1.0455 43.57 5000 0.2713 0.4088
1.0228 47.93 5500 0.2622 0.3960
0.9936 52.29 6000 0.2525 0.3796
0.968 56.64 6500 0.2506 0.3798
0.9704 61.0 7000 0.2481 0.3735
0.9552 65.36 7500 0.2394 0.3643
0.9417 69.72 8000 0.2350 0.3537
0.9215 74.07 8500 0.2326 0.3507
0.9097 78.43 9000 0.2277 0.3487
0.9003 82.79 9500 0.2230 0.3362
0.8857 87.15 10000 0.2246 0.3362
0.882 91.5 10500 0.2236 0.3315
0.8719 95.86 11000 0.2203 0.3271

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.1+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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F32
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