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wav2vec2-large-xls-r-300m-hsb-v3

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

  • Loss: 0.6549
  • Wer: 0.4827

Evaluation Commands

  1. To evaluate on mozilla-foundation/common_voice_8_0 with test split

python eval.py --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-hsb-v3 --dataset mozilla-foundation/common_voice_8_0 --config hsb --split test --log_outputs

  1. To evaluate on speech-recognition-community-v2/dev_data

Upper Sorbian (hsb) language not found in speech-recognition-community-v2/dev_data!

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.00045
  • 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
8.8951 3.23 100 3.6396 1.0
3.314 6.45 200 3.2331 1.0
3.1931 9.68 300 3.0947 0.9906
1.7079 12.9 400 0.8865 0.8499
0.6859 16.13 500 0.7994 0.7529
0.4804 19.35 600 0.7783 0.7069
0.3506 22.58 700 0.6904 0.6321
0.2695 25.81 800 0.6519 0.5926
0.222 29.03 900 0.7041 0.5720
0.1828 32.26 1000 0.6608 0.5513
0.1474 35.48 1100 0.7129 0.5319
0.1269 38.71 1200 0.6664 0.5056
0.1077 41.94 1300 0.6712 0.4942
0.0934 45.16 1400 0.6467 0.4879
0.0819 48.39 1500 0.6549 0.4827

Framework versions

  • Transformers 4.16.1
  • Pytorch 1.10.0+cu111
  • Datasets 1.18.2
  • Tokenizers 0.11.0
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Dataset used to train DrishtiSharma/wav2vec2-large-xls-r-300m-hsb-v3

Evaluation results