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update model card README.md
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README.md
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---
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license: mit
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base_model: Davlan/afro-xlmr-base
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: angela_shuffle_punctuation_regular_eval
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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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# angela_shuffle_punctuation_regular_eval
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This model is a fine-tuned version of [Davlan/afro-xlmr-base](https://huggingface.co/Davlan/afro-xlmr-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1556
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- Precision: 0.3691
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- Recall: 0.2130
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- F1: 0.2701
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- Accuracy: 0.9542
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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: 5e-05
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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=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.1804 | 1.0 | 1283 | 0.1530 | 0.4050 | 0.1046 | 0.1663 | 0.9579 |
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| 0.1608 | 2.0 | 2566 | 0.1481 | 0.4263 | 0.1280 | 0.1969 | 0.9584 |
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| 0.1499 | 3.0 | 3849 | 0.1462 | 0.4386 | 0.1367 | 0.2085 | 0.9586 |
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| 0.1389 | 4.0 | 5132 | 0.1515 | 0.4013 | 0.1862 | 0.2543 | 0.9567 |
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| 0.1253 | 5.0 | 6415 | 0.1556 | 0.3691 | 0.2130 | 0.2701 | 0.9542 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.2
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- Tokenizers 0.13.3
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