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Whisper small Luxembourgish

This model is a fine-tuned version of bofenghuang/whisper-small-cv11-german-punct on the google/fleurs lb_lu dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1857
  • Wer: 39.4990

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: 1e-05
  • train_batch_size: 8
  • eval_batch_size: 16
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 64
  • total_eval_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 5000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.0618 38.46 500 1.0104 43.2968
0.0055 76.92 1000 1.0684 40.1288
0.0024 115.38 1500 1.1056 40.9447
0.0014 153.85 2000 1.1280 39.7615
0.0013 192.31 2500 1.1415 39.9857
0.0008 230.77 3000 1.1573 39.7996
0.0006 269.23 3500 1.1682 40.0095
0.0006 307.69 4000 1.1769 39.7233
0.0005 346.15 4500 1.1826 39.5134
0.0004 384.62 5000 1.1857 39.4990

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.13.0+cu117
  • Datasets 2.7.1
  • Tokenizers 0.13.2
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Dataset used to train steja/whisper-small-luxembourgish

Evaluation results