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metadata
language:
  - fy
base_model: distil-small.en
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_6_1
metrics:
  - wer
model-index:
  - name: DistilFT-Frisian-10m
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_6_fy_NL
          type: mozilla-foundation/common_voice_6_1
          args: 'config: fy-NL, split: train-10m'
        metrics:
          - name: Wer
            type: wer
            value: 89.3637497772233

DistilFT-Frisian-10m

This model is a fine-tuned version of distil-small.en on the mozilla-foundation/common_voice_6_fy_NL dataset. It achieves the following results on the evaluation set:

  • Loss: 4.1946
  • Wer: 89.3637

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
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 200
  • training_steps: 3000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.1154 33.3333 500 3.7440 105.5534
0.0107 66.6667 1000 4.0814 88.1911
0.0 100.0 1500 4.1314 90.7432
0.0 133.3333 2000 4.1700 89.8663
0.0 166.6667 2500 4.1878 89.6061
0.0 200.0 3000 4.1946 89.3637

Framework versions

  • Transformers 4.41.0.dev0
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1