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DrishtiSharma/wav2vec2-large-xls-r-300m-bas-v1

🤗 Hugging Face sourceautomatic-speech-recognitionapache-2.06.3 GBother✓ 4 checksumsupdated today
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wav2vec2-large-xls-r-300m-bas-v1

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

  • Loss: 0.5997
  • Wer: 0.3870

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-bas-v1 --dataset mozilla-foundation/common_voice_8_0 --config bas --split test --log_outputs

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

Basaa (bas) language isn't available in speech-recognition-community-v2/dev_data

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.000111
  • 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: 100
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
12.7076 5.26 200 3.6361 1.0
3.1657 10.52 400 3.0101 1.0
2.3987 15.78 600 0.9125 0.6774
1.0079 21.05 800 0.6477 0.5352
0.7392 26.31 1000 0.5432 0.4929
0.6114 31.57 1200 0.5498 0.4639
0.5222 36.83 1400 0.5220 0.4561
0.4648 42.1 1600 0.5586 0.4289
0.4103 47.36 1800 0.5337 0.4082
0.3692 52.62 2000 0.5421 0.3861
0.3403 57.88 2200 0.5549 0.4096
0.3011 63.16 2400 0.5833 0.3925
0.2932 68.42 2600 0.5674 0.3815
0.2696 73.68 2800 0.5734 0.3889
0.2496 78.94 3000 0.5968 0.3985
0.2289 84.21 3200 0.5888 0.3893
0.2091 89.47 3400 0.5849 0.3852
0.2005 94.73 3600 0.5938 0.3875
0.1876 99.99 3800 0.5997 0.3870

Framework versions

  • Transformers 4.16.1
  • Pytorch 1.10.0+cu111
  • Datasets 1.18.2
  • Tokenizers 0.11.0