xls-r-uyghur-cv7 / README.md
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metadata
language:
  - ug
license: apache-2.0
tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_7_0
  - generated_from_trainer
datasets:
  - common_voice
model-index:
  - name: uyghur
    results: []

uyghur

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

  • Loss: 0.2266
  • Wer: 0.3655

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: 7.5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 2000
  • num_epochs: 50.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
3.6863 2.73 500 3.5362 1.0
3.1409 5.46 1000 3.1328 1.0
1.8979 8.2 1500 0.9715 0.8864
1.4859 10.93 2000 0.5234 0.7063
1.3388 13.66 2500 0.4094 0.6203
1.2531 16.39 3000 0.3596 0.5185
1.1992 19.13 3500 0.3221 0.4854
1.1589 21.86 4000 0.3040 0.4610
1.1345 24.59 4500 0.2907 0.4450
1.086 27.32 5000 0.2744 0.4299
1.0697 30.05 5500 0.2617 0.4148
1.0518 32.79 6000 0.2563 0.4033
1.0101 35.52 6500 0.2480 0.3934
1.0013 38.25 7000 0.2412 0.3855
0.9845 40.98 7500 0.2397 0.3771
0.9739 43.72 8000 0.2303 0.3726
0.9636 46.45 8500 0.2285 0.3687
0.9466 49.18 9000 0.2261 0.3648

Framework versions

  • Transformers 4.16.0.dev0
  • Pytorch 1.10.1+cu102
  • Datasets 1.18.2.dev0
  • Tokenizers 0.11.0