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language: - fi lisence: apache-2.0 tags: - automatic-speech-recognition - mozilla-foundation/common_voice_7_0 - generated_from_trainer - fi - speech - robust-speech-event datasets: - mozilla-foundation/common_voice_7_0 model-index: - name: XLS-R 1B Wav2Vec2 Finnish by Rasmus Toivanen results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 7 type: mozilla-foundation/common_voice_7_0 args: fi metrics: - name: Test WER type: wer value: 10.96 - name: Test CER type: cer value: 2.81

wav2vec2-xlsr-fi-train-aug-lm-1B

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1499
  • Wer: 0.1955

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: 0.0001
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 4
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.6473 0.29 400 0.2857 0.3825
0.6039 0.58 800 0.2459 0.3476
0.4757 0.87 1200 0.2338 0.3274
0.4473 1.15 1600 0.2246 0.3128
0.4322 1.44 2000 0.1962 0.2805
0.3961 1.73 2400 0.2070 0.2797
0.3642 2.02 2800 0.1790 0.2473
0.3561 2.31 3200 0.1769 0.2375
0.282 2.6 3600 0.1672 0.2263
0.2978 2.89 4000 0.1636 0.2192
0.2722 3.17 4400 0.1637 0.2102
0.2924 3.46 4800 0.1506 0.2021
0.2631 3.75 5200 0.1499 0.1955

Framework versions

  • Transformers 4.16.0.dev0
  • Pytorch 1.10.1+cu102
  • Datasets 1.17.1.dev0
  • Tokenizers 0.11.0