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DrishtiSharma/wav2vec2-large-xls-r-300m-or-d5

🤗 Hugging Face sourceautomatic-speech-recognitionapache-2.03.8 GBother✓ 4 checksumsupdated today
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wav2vec2-large-xls-r-300m-or-d5

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

  • Loss: 0.9571
  • Wer: 0.5450

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-or-d5 --dataset mozilla-foundation/common_voice_8_0 --config or --split test --log_outputs

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

python eval.py --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-or-d5 --dataset speech-recognition-community-v2/dev_data --config or --split validation --chunk_length_s 10 --stride_length_s 1

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: 800
  • num_epochs: 200
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
9.2958 12.5 300 4.9014 1.0
3.4065 25.0 600 3.5150 1.0
1.5402 37.5 900 0.8356 0.7249
0.6049 50.0 1200 0.7754 0.6349
0.4074 62.5 1500 0.7994 0.6217
0.3097 75.0 1800 0.8815 0.5985
0.2593 87.5 2100 0.8532 0.5754
0.2097 100.0 2400 0.9077 0.5648
0.1784 112.5 2700 0.9047 0.5668
0.1567 125.0 3000 0.9019 0.5728
0.1315 137.5 3300 0.9295 0.5827
0.1125 150.0 3600 0.9256 0.5681
0.1035 162.5 3900 0.9148 0.5496
0.0901 175.0 4200 0.9480 0.5483
0.0817 187.5 4500 0.9799 0.5516
0.079 200.0 4800 0.9571 0.5450

Framework versions

  • Transformers 4.16.2
  • Pytorch 1.10.0+cu111
  • Datasets 1.18.3
  • Tokenizers 0.11.0