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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_12_0 |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-large-xls-r-1b-frisian |
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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: common_voice_12_0 |
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type: common_voice_12_0 |
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config: fy-NL |
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split: validation |
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args: fy-NL |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.1685917915949865 |
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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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# wav2vec2-large-xls-r-1b-frisian |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the common_voice_12_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2748 |
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- Wer: 0.1686 |
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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: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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: 500 |
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- num_epochs: 50 |
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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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| 4.6809 | 2.1 | 250 | 2.0948 | 0.9948 | |
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| 1.2928 | 4.2 | 500 | 0.4505 | 0.4003 | |
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| 0.7887 | 6.3 | 750 | 0.3410 | 0.3287 | |
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| 0.7422 | 8.4 | 1000 | 0.3017 | 0.2756 | |
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| 0.7277 | 10.5 | 1250 | 0.3014 | 0.2624 | |
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| 0.6339 | 12.61 | 1500 | 0.2833 | 0.2398 | |
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| 0.5284 | 14.71 | 1750 | 0.2970 | 0.2404 | |
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| 0.5186 | 16.81 | 2000 | 0.2886 | 0.2400 | |
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| 0.515 | 18.91 | 2250 | 0.2891 | 0.2335 | |
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| 0.5199 | 21.01 | 2500 | 0.2985 | 0.2261 | |
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| 0.5228 | 23.11 | 2750 | 0.3026 | 0.2187 | |
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| 0.5102 | 25.21 | 3000 | 0.2829 | 0.1994 | |
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| 0.463 | 27.31 | 3250 | 0.2885 | 0.2012 | |
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| 0.5072 | 29.41 | 3500 | 0.2936 | 0.1971 | |
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| 0.4581 | 31.51 | 3750 | 0.2979 | 0.1912 | |
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| 0.4103 | 33.61 | 4000 | 0.2935 | 0.1875 | |
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| 0.3414 | 35.71 | 4250 | 0.2999 | 0.1860 | |
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| 0.4484 | 37.82 | 4500 | 0.2917 | 0.1810 | |
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| 0.3523 | 39.92 | 4750 | 0.2875 | 0.1759 | |
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| 0.3763 | 42.02 | 5000 | 0.2901 | 0.1758 | |
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| 0.2416 | 44.12 | 5250 | 0.2707 | 0.1740 | |
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| 0.1878 | 46.22 | 5500 | 0.2707 | 0.1717 | |
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| 0.1623 | 48.32 | 5750 | 0.2748 | 0.1686 | |
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### Framework versions |
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- Transformers 4.27.3 |
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- Pytorch 2.0.0+cu117 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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