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DrishtiSharma/wav2vec2-xls-r-300m-pa-IN-r5

🤗 Hugging Face sourceautomatic-speech-recognitionapache-2.015 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: 0.8881
  • Wer: 0.4175

Evaluation Commands

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

python eval.py --model_id DrishtiSharma/wav2vec2-xls-r-300m-pa-IN-r5 --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: 0.000111
  • train_batch_size: 16
  • eval_batch_size: 32
  • 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: 2000
  • num_epochs: 200.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
10.695 18.52 500 3.5681 1.0
3.2718 37.04 1000 2.3081 0.9643
0.8727 55.56 1500 0.7227 0.5147
0.3349 74.07 2000 0.7498 0.4959
0.2134 92.59 2500 0.7779 0.4720
0.1445 111.11 3000 0.8120 0.4594
0.1057 129.63 3500 0.8225 0.4610
0.0826 148.15 4000 0.8307 0.4351
0.0639 166.67 4500 0.8967 0.4316
0.0528 185.19 5000 0.8875 0.4238

Framework versions

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