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README.md
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---
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license: apache-2.0
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base_model: bert-base-multilingual-uncased
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tags:
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- generated_from_trainer
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metrics:
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- recall
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- accuracy
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model-index:
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- name: multibert_dataaugmentation
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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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# multibert_dataaugmentation
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This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5981
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- Precisions: 0.8870
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- Recall: 0.8815
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- F-measure: 0.8825
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- Accuracy: 0.9265
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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: 7.5e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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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: 14
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
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| 0.5651 | 1.0 | 284 | 0.4671 | 0.8381 | 0.7291 | 0.7488 | 0.8699 |
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| 0.2863 | 2.0 | 568 | 0.4120 | 0.8143 | 0.8209 | 0.8151 | 0.8946 |
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| 0.1717 | 3.0 | 852 | 0.3688 | 0.8778 | 0.8430 | 0.8579 | 0.9065 |
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| 0.1085 | 4.0 | 1136 | 0.4175 | 0.8609 | 0.8656 | 0.8624 | 0.9097 |
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| 0.0677 | 5.0 | 1420 | 0.4885 | 0.8728 | 0.8483 | 0.8588 | 0.9142 |
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| 0.0526 | 6.0 | 1704 | 0.5384 | 0.8672 | 0.8786 | 0.8672 | 0.9152 |
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| 0.0372 | 7.0 | 1988 | 0.4872 | 0.8766 | 0.8770 | 0.8759 | 0.9161 |
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| 0.0239 | 8.0 | 2272 | 0.5377 | 0.9011 | 0.8665 | 0.8799 | 0.9227 |
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| 0.0181 | 9.0 | 2556 | 0.5604 | 0.8846 | 0.8796 | 0.8813 | 0.9236 |
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| 0.0117 | 10.0 | 2840 | 0.5815 | 0.8695 | 0.8786 | 0.8700 | 0.9229 |
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| 0.008 | 11.0 | 3124 | 0.6035 | 0.8842 | 0.8701 | 0.8744 | 0.9206 |
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| 0.0047 | 12.0 | 3408 | 0.5789 | 0.8644 | 0.8815 | 0.8662 | 0.9232 |
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| 0.0037 | 13.0 | 3692 | 0.5891 | 0.8763 | 0.8782 | 0.8740 | 0.9259 |
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| 0.0026 | 14.0 | 3976 | 0.5981 | 0.8870 | 0.8815 | 0.8825 | 0.9265 |
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### Framework versions
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- Transformers 4.34.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.5
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- Tokenizers 0.14.1
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