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DrishtiSharma/wav2vec2-large-xls-r-300m-pa-IN-dx1

🤗 Hugging Face sourceautomatic-speech-recognitionapache-2.034 GBother✓ 2 checksumsupdated today
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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 - PA-IN dataset. It achieves the following results on the evaluation set:

  • Loss: 1.0855
  • Wer: 0.4755

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-pa-IN-dx1 --dataset mozilla-foundation/common_voice_8_0 --config pa-IN --split test --log_outputs

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

Punjabi language isn't available in speech-recognition-community-v2/dev_data

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0003
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1200
  • num_epochs: 100.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
3.4607 9.26 500 2.7746 1.0416
0.3442 18.52 1000 0.9114 0.5911
0.2213 27.78 1500 0.9687 0.5751
0.1242 37.04 2000 1.0204 0.5461
0.0998 46.3 2500 1.0250 0.5233
0.0727 55.56 3000 1.1072 0.5382
0.0605 64.81 3500 1.0588 0.5073
0.0458 74.07 4000 1.0818 0.5069
0.0338 83.33 4500 1.0948 0.5108
0.0223 92.59 5000 1.0986 0.4775

Framework versions

  • Transformers 4.17.0.dev0
  • Pytorch 1.10.2+cu102
  • Datasets 1.18.2.dev0
  • Tokenizers 0.11.0