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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-8-10m
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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: 0.7612841022711041
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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-8-10m
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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: 1.1618
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- Wer: 0.7613
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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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- 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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| 8.7106 | 6.25 | 50 | 4.0034 | 1.0 |
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| 3.4036 | 12.5 | 100 | 3.1030 | 1.0 |
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| 3.7265 | 18.75 | 150 | 3.0466 | 1.0 |
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| 3.2292 | 25.0 | 200 | 3.0166 | 1.0 |
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| 3.1305 | 31.25 | 250 | 2.9699 | 1.0 |
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| 3.0447 | 37.5 | 300 | 2.9144 | 1.0 |
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| 2.9037 | 43.75 | 350 | 2.2919 | 0.9998 |
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| 2.1115 | 50.0 | 400 | 1.3995 | 0.9429 |
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| 1.3456 | 56.25 | 450 | 1.1093 | 0.8435 |
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| 1.3206 | 62.5 | 500 | 1.1573 | 0.8112 |
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| 1.0078 | 68.75 | 550 | 1.1746 | 0.7757 |
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| 1.0674 | 75.0 | 600 | 1.1618 | 0.7613 |
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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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