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metadata
license: apache-2.0
tags:
  - generated_from_trainer
base_model: facebook/wav2vec2-large-xlsr-53
metrics:
  - wer
model-index:
  - name: wav2vec2-large-xlsr-53-breton
    results: []

wav2vec2-large-xlsr-53-breton

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: 0.9840
  • Wer: 0.5852
  • Cer: 0.2130

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: 6e-05
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.08
  • num_epochs: 50
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
11.8947 2.56 250 3.4769 1.0 0.9862
3.1668 5.13 500 3.0459 1.0 0.9862
2.6491 7.69 750 1.6416 0.9319 0.4441
1.4107 10.26 1000 1.1000 0.7751 0.2852
0.9989 12.82 1250 0.9827 0.7092 0.2578
0.8238 15.38 1500 0.9543 0.6864 0.2476
0.7193 17.95 1750 0.9241 0.6547 0.2371
0.6377 20.51 2000 0.9296 0.6452 0.2352
0.5865 23.08 2250 0.9287 0.6320 0.2301
0.541 25.64 2500 0.9359 0.6205 0.2231
0.4988 28.21 2750 0.9850 0.6149 0.2244
0.4691 30.77 3000 0.9566 0.6065 0.2192
0.4568 33.33 3250 0.9653 0.6019 0.2175
0.4485 35.9 3500 0.9760 0.5949 0.2175
0.4219 38.46 3750 0.9824 0.5926 0.2177
0.397 41.03 4000 0.9669 0.5885 0.2138
0.3912 43.59 4250 0.9857 0.5908 0.2145
0.3764 46.15 4500 0.9937 0.5886 0.2145
0.3742 48.72 4750 0.9840 0.5852 0.2130

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.0