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README.md
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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_8_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-cv-8-1h
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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_8_0
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type: common_voice_8_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: 0.23732323953720896
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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-cv-8-1h
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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_8_0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4120
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- Wer: 0.2373
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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: 6e-05
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- train_batch_size: 32
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 80
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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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| 6.2987 | 4.35 | 100 | 3.0210 | 1.0 |
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| 3.1424 | 8.7 | 200 | 2.9611 | 1.0 |
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| 2.6299 | 13.04 | 300 | 0.9929 | 0.8377 |
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| 1.3134 | 17.39 | 400 | 0.5679 | 0.5264 |
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| 0.9747 | 21.74 | 500 | 0.4516 | 0.3764 |
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| 0.8755 | 26.09 | 600 | 0.4515 | 0.3403 |
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| 0.7227 | 30.43 | 700 | 0.4169 | 0.3211 |
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| 0.6634 | 34.78 | 800 | 0.4159 | 0.2962 |
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| 0.5568 | 39.13 | 900 | 0.4081 | 0.2795 |
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| 0.7943 | 43.48 | 1000 | 0.4090 | 0.2709 |
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| 0.5537 | 47.83 | 1100 | 0.4239 | 0.2649 |
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| 0.5596 | 52.17 | 1200 | 0.4029 | 0.2561 |
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| 0.5523 | 56.52 | 1300 | 0.4073 | 0.2524 |
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| 0.4579 | 60.87 | 1400 | 0.4098 | 0.2470 |
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| 0.6477 | 65.22 | 1500 | 0.4099 | 0.2446 |
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| 0.4957 | 69.57 | 1600 | 0.4167 | 0.2475 |
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| 0.3246 | 73.91 | 1700 | 0.4146 | 0.2389 |
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| 0.3937 | 78.26 | 1800 | 0.4120 | 0.2373 |
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### Framework versions
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- Transformers 4.28.1
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- Pytorch 2.0.0+cu117
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- Datasets 2.11.0
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- Tokenizers 0.13.3
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