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anuragshas/wav2vec2-xls-r-300m-mr-cv9-with-lm

🤗 Hugging Face sourceautomatic-speech-recognitionapache-2.022 GBother✓ 4 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_9_0 - MR dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3642
  • Wer: 0.4190
  • Cer: 0.0946

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: 7.5e-05
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • training_steps: 6124
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
3.5184 12.9 400 3.4210 1.0 1.0
2.3797 25.81 800 1.1068 0.8389 0.2584
1.5022 38.71 1200 0.5278 0.6280 0.1517
1.3181 51.61 1600 0.4254 0.5587 0.1297
1.2037 64.52 2000 0.3836 0.5143 0.1176
1.1245 77.42 2400 0.3643 0.4871 0.1111
1.0582 90.32 2800 0.3562 0.4676 0.1062
1.0027 103.23 3200 0.3530 0.4625 0.1058
0.9382 116.13 3600 0.3388 0.4442 0.1002
0.8915 129.03 4000 0.3430 0.4427 0.1000
0.853 141.94 4400 0.3536 0.4375 0.1000
0.8127 154.84 4800 0.3511 0.4344 0.0986
0.7861 167.74 5200 0.3595 0.4372 0.0993
0.7619 180.65 5600 0.3628 0.4316 0.0985
0.7537 193.55 6000 0.3633 0.4174 0.0943

Framework versions

  • Transformers 4.19.0.dev0
  • Pytorch 1.11.0+cu102
  • Datasets 2.1.1.dev0
  • Tokenizers 0.12.1