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URDU-ASR-25-EPOCH

This model is a fine-tuned version of Shehryar718/URDU-ASR on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7833
  • Wer: 0.4924
  • Cer: 0.2059

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: 0.00025
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 25
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
3.5981 1.0 341 0.7487 0.5453 0.2200
0.2559 2.0 683 0.7159 0.5086 0.2077
0.3018 3.0 1024 0.7059 0.5457 0.2325
0.2848 4.0 1366 0.6575 0.5464 0.2350
0.2599 5.0 1707 0.6924 0.5436 0.2346
0.2479 6.0 2049 0.6785 0.5372 0.2254
0.2363 7.0 2390 0.7261 0.5356 0.2284
0.2225 8.0 2732 0.7228 0.5199 0.2268
0.2038 9.0 3073 0.7688 0.5248 0.2218
0.1944 10.0 3415 0.7385 0.5384 0.2298
0.1908 11.0 3756 0.7569 0.5325 0.2283
0.1899 12.0 4098 0.7458 0.5088 0.2106
0.1728 13.0 4439 0.7386 0.5326 0.2236
0.1762 14.0 4781 0.7521 0.5297 0.2265
0.1762 15.0 5122 0.7338 0.5197 0.2184
0.1666 16.0 5464 0.7795 0.5294 0.2149
0.1605 17.0 5805 0.7622 0.5092 0.2211
0.1539 18.0 6147 0.7756 0.5144 0.2132
0.1472 19.0 6488 0.7522 0.4989 0.2094
0.1399 20.0 6830 0.7691 0.5144 0.2171
0.1341 21.0 7171 0.7673 0.4992 0.2079
0.1278 22.0 7513 0.7807 0.4889 0.2005
0.1235 23.0 7854 0.7924 0.4932 0.2060
0.1189 24.0 8196 0.7876 0.4954 0.2060
0.1167 24.96 8525 0.7833 0.4924 0.2059

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.1.0+cu121
  • Datasets 2.14.4
  • Tokenizers 0.14.1
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Finetuned from

Evaluation results