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--- |
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language: |
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- fy |
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base_model: distil-small.en |
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tags: |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_6_1 |
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metrics: |
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- wer |
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model-index: |
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- name: DistilFT-Frisian-10h |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: mozilla-foundation/common_voice_6_fy_NL |
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type: mozilla-foundation/common_voice_6_1 |
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args: 'config: fy-NL, split: train-10h' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 26.911423988593835 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# DistilFT-Frisian-10h |
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This model is a fine-tuned version of [distil-small.en](https://huggingface.co./distil-small.en) on the mozilla-foundation/common_voice_6_fy_NL dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5755 |
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- Wer: 26.9114 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 300 |
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- training_steps: 5000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:------:|:----:|:---------------:|:-------:| |
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| 0.9504 | 0.5348 | 500 | 1.0939 | 57.4122 | |
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| 0.4656 | 1.0695 | 1000 | 0.8241 | 45.7316 | |
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| 0.4533 | 1.6043 | 1500 | 0.7285 | 41.3474 | |
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| 0.1745 | 2.1390 | 2000 | 0.6875 | 37.7009 | |
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| 0.1701 | 2.6738 | 2500 | 0.6261 | 34.7603 | |
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| 0.0709 | 3.2086 | 3000 | 0.6566 | 33.4415 | |
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| 0.0731 | 3.7433 | 3500 | 0.5880 | 30.5650 | |
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| 0.0234 | 4.2781 | 4000 | 0.5949 | 28.8754 | |
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| 0.0192 | 4.8128 | 4500 | 0.5799 | 27.7063 | |
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| 0.0038 | 5.3476 | 5000 | 0.5755 | 26.9114 | |
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### Framework versions |
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- Transformers 4.41.0.dev0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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