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xlsr-a-nomo

Automatic Speech Recognition
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Safetensors
wav2vec2
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metadata
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: xlsr-a-nomo
    results: []

xlsr-a-nomo

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6748
  • Wer: 0.3390

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: 0.0004
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 132
  • num_epochs: 100
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
4.3851 2.3529 200 2.4270 1.0
1.3933 4.7059 400 0.5187 0.6193
0.2417 7.0588 600 0.4328 0.4403
0.1174 9.4118 800 0.4113 0.4186
0.08 11.7647 1000 0.3914 0.3589
0.0509 14.1176 1200 0.4065 0.3665
0.0445 16.4706 1400 0.4714 0.3636
0.0329 18.8235 1600 0.3930 0.3561
0.0315 21.1765 1800 0.5501 0.3655
0.0298 23.5294 2000 0.4462 0.3561
0.0366 25.8824 2200 0.4993 0.3447
0.0259 28.2353 2400 0.5077 0.3561
0.0197 30.5882 2600 0.5029 0.3466
0.0229 32.9412 2800 0.4760 0.3400
0.0174 35.2941 3000 0.5118 0.3475
0.0102 37.6471 3200 0.5630 0.3428
0.0104 40.0 3400 0.5598 0.3400
0.015 42.3529 3600 0.5226 0.3428
0.0102 44.7059 3800 0.5421 0.3513
0.012 47.0588 4000 0.5936 0.3456
0.0101 49.4118 4200 0.5772 0.3485
0.009 51.7647 4400 0.5759 0.3438
0.0104 54.1176 4600 0.5755 0.3400
0.0118 56.4706 4800 0.5868 0.3362
0.0118 58.8235 5000 0.6174 0.3456
0.0109 61.1765 5200 0.6037 0.3390
0.0086 63.5294 5400 0.5903 0.3447
0.0039 65.8824 5600 0.5894 0.3428
0.0058 68.2353 5800 0.6388 0.3428
0.0044 70.5882 6000 0.6378 0.3390
0.0032 72.9412 6200 0.6868 0.3409
0.0057 75.2941 6400 0.6439 0.3419
0.0034 77.6471 6600 0.6888 0.3381
0.0022 80.0 6800 0.7217 0.3381
0.0032 82.3529 7000 0.5946 0.3371
0.0033 84.7059 7200 0.6650 0.3390
0.0018 87.0588 7400 0.6844 0.3371
0.0026 89.4118 7600 0.7199 0.3409
0.0028 91.7647 7800 0.6868 0.3381
0.002 94.1176 8000 0.6752 0.3409
0.0013 96.4706 8200 0.6788 0.3390
0.0011 98.8235 8400 0.6748 0.3390

Framework versions

  • Transformers 4.47.0.dev0
  • Pytorch 2.4.0
  • Datasets 3.0.1
  • Tokenizers 0.20.0