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infinitejoy/wav2vec2-large-xls-r-300m-bulgarian

🤗 Hugging Face sourceautomatic-speech-recognitionapache-2.021 GBother✓ 2 checksumsupdated today
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wav2vec2-large-xls-r-300m-bulgarian

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - BG dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4487
  • Wer: 0.4674

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

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: 500
  • num_epochs: 100.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
2.9774 6.33 500 2.9769 1.0
1.3453 12.66 1000 0.6523 0.6980
1.1658 18.99 1500 0.5636 0.6359
1.0797 25.32 2000 0.5004 0.5759
1.044 31.65 2500 0.4958 0.5569
0.9915 37.97 3000 0.4971 0.5350
0.9429 44.3 3500 0.4829 0.5229
0.9266 50.63 4000 0.4515 0.5074
0.8965 56.96 4500 0.4599 0.5039
0.878 63.29 5000 0.4735 0.4954
0.8494 69.62 5500 0.4460 0.4878
0.8343 75.95 6000 0.4510 0.4795
0.8236 82.28 6500 0.4538 0.4789
0.8069 88.61 7000 0.4526 0.4748
0.7958 94.94 7500 0.4496 0.4700

Framework versions

  • Transformers 4.16.0.dev0
  • Pytorch 1.10.1+cu102
  • Datasets 1.17.1.dev0
  • Tokenizers 0.11.0