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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - common_voice
model-index:
  - name: wav2vec2-large-xlsr-53-demo1
    results: []

wav2vec2-large-xlsr-53-demo1

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the common_voice dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9692
  • Wer: 0.8462

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: 0.0003
  • train_batch_size: 5
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 10
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Wer
12.978 0.06 100 3.5377 1.0
3.5026 0.13 200 3.4366 1.0
3.4084 0.19 300 3.3831 1.0
3.3551 0.26 400 3.2563 1.0
3.2668 0.32 500 3.2109 1.0
2.9398 0.38 600 2.4548 0.9987
2.2204 0.45 700 1.8870 1.0135
1.7401 0.51 800 1.6816 1.0247
1.5748 0.57 900 1.4741 0.9953
1.4539 0.64 1000 1.4573 0.9852
1.3612 0.7 1100 1.3534 0.9529
1.3328 0.77 1200 1.3380 0.9320
1.2459 0.83 1300 1.2984 0.9247
1.1976 0.89 1400 1.2515 0.9252
1.1593 0.96 1500 1.2345 0.9030
1.1094 1.02 1600 1.2135 0.9305
1.0485 1.09 1700 1.2045 0.9121
0.9893 1.15 1800 1.1876 0.8990
1.0099 1.21 1900 1.1663 0.8889
0.982 1.28 2000 1.1674 0.8901
0.9975 1.34 2100 1.1181 0.8812
0.952 1.4 2200 1.1119 0.8817
0.9311 1.47 2300 1.0786 0.8773
0.9398 1.53 2400 1.1016 0.8720
0.9148 1.6 2500 1.0878 0.8778
0.9114 1.66 2600 1.1004 0.8712
0.902 1.72 2700 1.0223 0.8744
0.8978 1.79 2800 1.0616 0.8459
0.8675 1.85 2900 1.0974 0.8643
0.8373 1.92 3000 1.0389 0.8547
0.8575 1.98 3100 1.0388 0.8480
0.8313 2.04 3200 1.0001 0.8648
0.7357 2.11 3300 1.0222 0.8705
0.743 2.17 3400 1.0859 0.8765
0.7306 2.23 3500 1.0109 0.8515
0.7525 2.3 3600 0.9942 0.8619
0.7308 2.36 3700 1.0004 0.8578
0.7266 2.43 3800 1.0003 0.8497
0.737 2.49 3900 1.0146 0.8505
0.7202 2.55 4000 1.0172 0.8653
0.6945 2.62 4100 0.9894 0.8415
0.6633 2.68 4200 0.9894 0.8496
0.6972 2.75 4300 0.9805 0.8505
0.6872 2.81 4400 0.9939 0.8509
0.7238 2.87 4500 0.9740 0.8532
0.6847 2.94 4600 0.9692 0.8462

Framework versions

  • Transformers 4.11.3
  • Pytorch 1.10.0+cu111
  • Datasets 1.14.0
  • Tokenizers 0.10.3