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update model card README.md
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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
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model-index:
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- name: wav2vec2-large-xls-r-300m-dutch-baseline
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results: []
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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-300m-dutch-baseline
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5107
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- Wer: 0.2674
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- Cer: 0.0863
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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: 0.0003
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 2
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 32
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- total_eval_batch_size: 8
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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: 30
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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 | Cer |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
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| 3.655 | 1.31 | 400 | 0.9337 | 0.7332 | 0.2534 |
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| 0.42 | 2.61 | 800 | 0.5018 | 0.4115 | 0.1374 |
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| 0.2267 | 3.92 | 1200 | 0.4776 | 0.3791 | 0.1259 |
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| 0.1624 | 5.23 | 1600 | 0.4807 | 0.3590 | 0.1208 |
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| 0.135 | 6.54 | 2000 | 0.4899 | 0.3417 | 0.1121 |
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| 0.1179 | 7.84 | 2400 | 0.5096 | 0.3445 | 0.1133 |
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| 0.1035 | 9.15 | 2800 | 0.4563 | 0.3455 | 0.1129 |
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| 0.092 | 10.46 | 3200 | 0.5061 | 0.3382 | 0.1127 |
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| 0.0804 | 11.76 | 3600 | 0.4969 | 0.3285 | 0.1088 |
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| 0.0748 | 13.07 | 4000 | 0.5274 | 0.3380 | 0.1114 |
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| 0.0669 | 14.38 | 4400 | 0.5201 | 0.3115 | 0.1028 |
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| 0.0588 | 15.69 | 4800 | 0.5238 | 0.3212 | 0.1054 |
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| 0.0561 | 16.99 | 5200 | 0.5273 | 0.3185 | 0.1044 |
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| 0.0513 | 18.3 | 5600 | 0.5577 | 0.3032 | 0.1010 |
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| 0.0476 | 19.61 | 6000 | 0.5298 | 0.3050 | 0.1008 |
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| 0.0408 | 20.91 | 6400 | 0.5725 | 0.2982 | 0.0984 |
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| 0.0376 | 22.22 | 6800 | 0.5605 | 0.2953 | 0.0966 |
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| 0.0339 | 23.53 | 7200 | 0.5419 | 0.2865 | 0.0938 |
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| 0.0315 | 24.84 | 7600 | 0.5530 | 0.2782 | 0.0915 |
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| 0.0286 | 26.14 | 8000 | 0.5354 | 0.2788 | 0.0917 |
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| 0.0259 | 27.45 | 8400 | 0.5245 | 0.2715 | 0.0878 |
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| 0.0231 | 28.76 | 8800 | 0.5107 | 0.2674 | 0.0863 |
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### Framework versions
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- Transformers 4.17.0
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- Pytorch 1.12.0+cu102
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- Datasets 2.7.1
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- Tokenizers 0.13.2
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