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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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metrics:
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- wer
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model-index:
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- name: seq-xls-r-fleurs_nl-run2-asr_af-run15
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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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# seq-xls-r-fleurs_nl-run2-asr_af-run15
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This model is a fine-tuned version of [lucas-meyer/xls-r-fleurs_nl-run2](https://huggingface.co/lucas-meyer/xls-r-fleurs_nl-run2) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4339
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- Wer: 0.3560
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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: 8
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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: 16
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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 |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| 11.2739 | 0.29 | 50 | 5.2927 | 1.0 |
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| 3.8398 | 0.59 | 100 | 3.3122 | 1.0 |
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| 3.1152 | 0.88 | 150 | 3.0188 | 1.0 |
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| 2.9857 | 1.17 | 200 | 2.9748 | 0.9998 |
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| 2.8793 | 1.47 | 250 | 2.7253 | 1.0 |
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| 2.0828 | 1.76 | 300 | 1.5219 | 0.9291 |
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| 1.1713 | 2.05 | 350 | 0.8089 | 0.6017 |
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| 0.74 | 2.35 | 400 | 0.6447 | 0.5613 |
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| 0.6223 | 2.64 | 450 | 0.5806 | 0.4899 |
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| 0.5661 | 2.93 | 500 | 0.5890 | 0.4928 |
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| 0.4624 | 3.23 | 550 | 0.5796 | 0.4767 |
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| 0.4107 | 3.52 | 600 | 0.5077 | 0.4624 |
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| 0.3755 | 3.81 | 650 | 0.4489 | 0.4109 |
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| 0.3255 | 4.11 | 700 | 0.4474 | 0.3887 |
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| 0.2728 | 4.4 | 750 | 0.4477 | 0.3958 |
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| 0.2756 | 4.69 | 800 | 0.4477 | 0.3841 |
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| 0.282 | 4.99 | 850 | 0.4243 | 0.3914 |
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| 0.2362 | 5.28 | 900 | 0.4756 | 0.4081 |
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| 0.2262 | 5.57 | 950 | 0.4554 | 0.3824 |
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| 0.2315 | 5.87 | 1000 | 0.3963 | 0.3721 |
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| 0.2016 | 6.16 | 1050 | 0.4290 | 0.3734 |
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| 0.1772 | 6.45 | 1100 | 0.4419 | 0.3649 |
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| 0.1835 | 6.74 | 1150 | 0.4339 | 0.3560 |
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### Framework versions
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- Transformers 4.28.0
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- Pytorch 2.0.1+cu117
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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