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

Automatic Speech Recognition
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wav2vec2
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wav2vec2-xlsr-53-ft-btb-ccv-cy / README.md
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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: nan
  • Wer: 1.0

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: 8
  • 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: 20000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
4.7126 0.0321 500 1.7047 0.9346
1.0533 0.0641 1000 1.1487 0.7907
0.8268 0.0962 1500 1.0602 0.7815
0.7188 0.1283 2000 0.9336 0.6717
0.6725 0.1603 2500 0.9304 0.6561
0.6295 0.1924 3000 0.8600 0.6257
0.6003 0.2244 3500 0.8395 0.6113
0.5847 0.2565 4000 0.7884 0.5861
0.5521 0.2886 4500 0.7741 0.5687
0.5477 0.3206 5000 0.7594 0.5536
0.5346 0.3527 5500 0.7482 0.5394
0.5154 0.3848 6000 0.7294 0.5352
0.492 0.4168 6500 0.7248 0.5493
0.4759 0.4489 7000 0.7077 0.5134
0.4655 0.4810 7500 0.6739 0.5064
0.4594 0.5130 8000 0.6575 0.5067
0.4538 0.5451 8500 0.6493 0.5003
0.4739 0.5771 9000 0.7677 0.5239
0.695 0.6092 9500 nan 1.0
0.0 0.6413 10000 nan 1.0
0.0 0.6733 10500 nan 1.0
0.0 0.7054 11000 nan 1.0
0.0 0.7375 11500 nan 1.0
0.0 0.7695 12000 nan 1.0
0.0 0.8016 12500 nan 1.0
0.0 0.8337 13000 nan 1.0
0.0 0.8657 13500 nan 1.0
0.0 0.8978 14000 nan 1.0
0.0 0.9298 14500 nan 1.0
0.0 0.9619 15000 nan 1.0
0.0 0.9940 15500 nan 1.0
0.0 1.0260 16000 nan 1.0
0.0 1.0581 16500 nan 1.0
0.0 1.0902 17000 nan 1.0
0.0 1.1222 17500 nan 1.0
0.0 1.1543 18000 nan 1.0
0.0 1.1864 18500 nan 1.0
0.0 1.2184 19000 nan 1.0
0.0 1.2505 19500 nan 1.0
0.0 1.2825 20000 nan 1.0

Framework versions

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