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wav2vec2-xlsr-53-ft-btb-ccv-cy

Automatic Speech Recognition
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metadata
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
  - automatic-speech-recognition
  - DewiBrynJones/banc-trawsgrifiadau-bangor-clean-with-ccv
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: wav2vec2-xlsr-53-ft-btb-ccv-cy
    results: []

wav2vec2-xlsr-53-ft-btb-ccv-cy

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the DEWIBRYNJONES/BANC-TRAWSGRIFIADAU-BANGOR-CLEAN-WITH-CCV - DEFAULT dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7821
  • Wer: 0.4576

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: 16
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 600
  • training_steps: 6000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
No log 0.0631 200 3.0428 1.0
No log 0.1262 400 3.1056 1.0
4.232 0.1893 600 1.2093 0.8286
4.232 0.2524 800 1.0886 0.7325
1.0379 0.3156 1000 0.9018 0.6730
1.0379 0.3787 1200 0.8131 0.5803
1.0379 0.4418 1400 0.7567 0.5544
0.8008 0.5049 1600 0.7040 0.5138
0.8008 0.5680 1800 0.6949 0.5236
0.7212 0.6311 2000 0.6722 0.4993
0.7212 0.6942 2200 0.6404 0.4762
0.7212 0.7573 2400 0.6336 0.4686
0.6639 0.8204 2600 0.5933 0.4587
0.6639 0.8836 2800 0.5996 0.4544
0.6278 0.9467 3000 0.5639 0.4242
0.6278 1.0098 3200 0.5665 0.4228
0.6278 1.0729 3400 0.5476 0.4191
0.5528 1.1360 3600 0.5440 0.4189
0.5528 1.1991 3800 0.5298 0.4071
0.5103 1.2622 4000 0.5384 0.4025
0.5103 1.3253 4200 0.5311 0.3998
0.5103 1.3885 4400 0.5396 0.4039
0.5194 1.4516 4600 0.5502 0.4049
0.5194 1.5147 4800 0.6632 0.4365
0.6034 1.5778 5000 0.7075 0.4368
0.6034 1.6409 5200 0.7466 0.4419
0.6034 1.7040 5400 0.7625 0.4498
0.74 1.7671 5600 0.7502 0.4475
0.74 1.8302 5800 0.7740 0.4596
0.7844 1.8933 6000 0.7821 0.4576

Framework versions

  • Transformers 4.44.0
  • Pytorch 2.4.0+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1