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This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - HI dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8111
  • Wer: 0.5177

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
4.9733 2.59 500 5.0697 1.0
3.3839 5.18 1000 3.3518 1.0
2.0596 7.77 1500 1.3992 0.7869
1.6102 10.36 2000 1.0712 0.6754
1.4587 12.95 2500 0.9280 0.6361
1.3667 15.54 3000 0.9281 0.6155
1.3042 18.13 3500 0.9037 0.5921
1.2544 20.73 4000 0.8996 0.5824
1.2274 23.32 4500 0.8934 0.5797
1.1763 25.91 5000 0.8643 0.5760
1.149 28.5 5500 0.8251 0.5544
1.1207 31.09 6000 0.8506 0.5527
1.091 33.68 6500 0.8370 0.5366
1.0613 36.27 7000 0.8345 0.5352
1.0495 38.86 7500 0.8380 0.5321
1.0345 41.45 8000 0.8285 0.5269
1.0297 44.04 8500 0.7836 0.5141
1.027 46.63 9000 0.8120 0.5180
0.9876 49.22 9500 0.8109 0.5188

Framework versions

  • Transformers 4.16.0.dev0
  • Pytorch 1.10.1+cu113
  • Datasets 1.18.1.dev0
  • Tokenizers 0.11.0
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Dataset used to train shivam/xls-r-300m-hindi

Evaluation results

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