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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 - SL dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2855
  • Wer: 0.2401

##Evaluation Commands

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

python eval.py --model_id DrishtiSharma/wav2vec2-xls-r-sl-a2 --dataset mozilla-foundation/common_voice_8_0 --config sl --split test --log_outputs

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

Votic language not found in speech-recognition-community-v2/dev_data

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 7e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 100.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
6.9294 6.1 500 2.9712 1.0
2.8305 12.2 1000 1.7073 0.9479
1.4795 18.29 1500 0.5756 0.6397
1.3433 24.39 2000 0.4968 0.5424
1.1766 30.49 2500 0.4185 0.4743
1.0017 36.59 3000 0.3303 0.3578
0.9358 42.68 3500 0.3003 0.3051
0.8358 48.78 4000 0.3045 0.2884
0.7647 54.88 4500 0.2866 0.2677
0.7482 60.98 5000 0.2829 0.2585
0.6943 67.07 5500 0.2782 0.2478
0.6586 73.17 6000 0.2911 0.2537
0.6425 79.27 6500 0.2817 0.2462
0.6067 85.37 7000 0.2910 0.2436
0.5974 91.46 7500 0.2875 0.2430
0.5812 97.56 8000 0.2852 0.2396

Framework versions

  • Transformers 4.17.0.dev0
  • Pytorch 1.10.2+cu102
  • Datasets 1.18.2.dev0
  • Tokenizers 0.11.0
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Dataset used to train DrishtiSharma/wav2vec2-xls-r-sl-a2

Evaluation results