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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: xlm-roberta-base
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- precision
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- recall
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- f1
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model-index:
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- name: xlmr-nli-indoindo
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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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# xlmr-nli-indoindo
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6699
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- Accuracy: 0.7701
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- Precision: 0.7701
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- Recall: 0.7701
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- F1: 0.7693
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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: 3e-06
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- train_batch_size: 6
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- eval_batch_size: 6
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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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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 6
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
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| 1.0444 | 1.0 | 1722 | 0.8481 | 0.6463 | 0.6463 | 0.6463 | 0.6483 |
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| 0.7958 | 2.0 | 3444 | 0.7483 | 0.7369 | 0.7369 | 0.7369 | 0.7353 |
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| 0.7175 | 3.0 | 5166 | 0.6812 | 0.7579 | 0.7579 | 0.7579 | 0.7576 |
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| 0.66 | 4.0 | 6888 | 0.6293 | 0.7679 | 0.7679 | 0.7679 | 0.7674 |
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| 0.6056 | 5.0 | 8610 | 0.6459 | 0.7651 | 0.7651 | 0.7651 | 0.7640 |
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| 0.5769 | 6.0 | 10332 | 0.6699 | 0.7701 | 0.7701 | 0.7701 | 0.7693 |
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### Framework versions
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- Transformers 4.31.0.dev0
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- Pytorch 2.0.0
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- Datasets 2.1.0
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- Tokenizers 0.13.3
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