badrex / xls-r-300-cv17-polish

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Model's Last Updated: June 11 2024
automatic-speech-recognition

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xls-r-300-cv17-polish

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3950
  • Wer: 0.2789
  • Cer: 0.0606
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: 0.0003
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • 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: 500
  • num_epochs: 50
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss Wer Cer
4.0552 1.6 100 4.2577 1.0 1.0
3.2887 3.2 200 3.2578 1.0 1.0
3.1481 4.8 300 3.1634 1.0 1.0
0.742 6.4 400 0.6905 0.6579 0.1603
0.4458 8.0 500 0.4687 0.4969 0.1169
0.2013 9.6 600 0.4327 0.4055 0.0929
0.2196 11.2 700 0.4180 0.4006 0.0903
0.1264 12.8 800 0.4360 0.3943 0.0898
0.1678 14.4 900 0.4157 0.3635 0.0818
0.1306 16.0 1000 0.3980 0.3667 0.0814
0.0471 17.6 1100 0.4206 0.3630 0.0828
0.1018 19.2 1200 0.3908 0.3522 0.0796
0.0637 20.8 1300 0.4277 0.3517 0.0785
0.1134 22.4 1400 0.4209 0.3373 0.0750
0.0709 24.0 1500 0.4255 0.3387 0.0766
0.046 25.6 1600 0.4301 0.3352 0.0746
0.065 27.2 1700 0.4087 0.3278 0.0724
0.0625 28.8 1800 0.4203 0.3454 0.0761
0.0344 30.4 1900 0.4317 0.3203 0.0714
0.0667 32.0 2000 0.4319 0.3258 0.0725
0.0305 33.6 2100 0.4260 0.3216 0.0716
0.04 35.2 2200 0.4172 0.3175 0.0697
0.0454 36.8 2300 0.4182 0.2996 0.0658
0.0273 38.4 2400 0.3966 0.2970 0.0654
0.0463 40.0 2500 0.4111 0.2926 0.0644
0.0321 41.6 2600 0.4094 0.2893 0.0633
0.0197 43.2 2700 0.3953 0.2846 0.0622
0.0306 44.8 2800 0.3980 0.2817 0.0613
0.0459 46.4 2900 0.3937 0.2807 0.0613
0.006 48.0 3000 0.3953 0.2780 0.0604
0.0329 49.6 3100 0.3950 0.2789 0.0606
Framework versions
  • Transformers 4.42.0.dev0
  • Pytorch 2.3.1+cu121
  • Datasets 2.19.2
  • Tokenizers 0.19.1

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