wav2vec2-large-xls-r-300m-Arabic-colab

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0021
  • Wer: 0.0191
  • Cer: 0.0072

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: 0.0005
  • train_batch_size: 16
  • eval_batch_size: 6
  • 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: 250
  • num_epochs: 30.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
17.5531 1.0 51 5.2205 1.0 1.0
3.9441 2.0 102 3.1378 1.0 1.0
3.1686 3.0 153 3.1191 1.0 1.0
3.1558 4.0 204 3.1101 1.0 1.0
3.1286 5.0 255 3.0171 1.0 1.0
3.0755 6.0 306 2.9542 1.0 1.0
2.9533 7.0 357 2.8221 1.0 1.0
2.5924 8.0 408 2.1453 1.0 0.9771
1.8657 9.0 459 1.1540 0.9094 0.7057
0.9519 10.0 510 0.4219 0.6767 0.2782
0.4752 11.0 561 0.1646 0.3416 0.0870
0.2402 12.0 612 0.0551 0.0899 0.0255
0.1512 13.0 663 0.0307 0.0586 0.0167
0.0906 14.0 714 0.0172 0.0541 0.0161
0.0711 15.0 765 0.0141 0.0444 0.0125
0.0561 16.0 816 0.0114 0.0269 0.0065
0.048 17.0 867 0.0090 0.0338 0.0110
0.0452 18.0 918 0.0072 0.0235 0.0080
0.0349 19.0 969 0.0073 0.0207 0.0062
0.0333 20.0 1020 0.0054 0.0183 0.0055
0.0275 21.0 1071 0.0050 0.0280 0.0087
0.0262 22.0 1122 0.0039 0.0251 0.0088
0.0241 23.0 1173 0.0039 0.0302 0.0110
0.0216 24.0 1224 0.0035 0.0243 0.0086
0.019 25.0 1275 0.0033 0.0250 0.0091
0.0178 26.0 1326 0.0027 0.0238 0.0089
0.0169 27.0 1377 0.0025 0.0220 0.0080
0.0168 28.0 1428 0.0024 0.0175 0.0060
0.015 29.0 1479 0.0021 0.0194 0.0071
0.0131 30.0 1530 0.0021 0.0191 0.0072

Framework versions

  • Transformers 4.26.1
  • Pytorch 1.13.1+cu116
  • Datasets 2.10.0
  • Tokenizers 0.13.2
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