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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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- 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: mbert-targin-final
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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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# mbert-targin-final
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This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9847
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- Accuracy: 0.7025
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- Precision: 0.6490
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- Recall: 0.6487
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- F1: 0.6489
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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: 1e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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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: 10
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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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| No log | 1.0 | 296 | 0.5774 | 0.7091 | 0.6506 | 0.6378 | 0.6426 |
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| 0.5912 | 2.0 | 592 | 0.5316 | 0.7376 | 0.6880 | 0.6767 | 0.6814 |
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| 0.5912 | 3.0 | 888 | 0.5511 | 0.7253 | 0.6692 | 0.6293 | 0.6378 |
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| 0.4844 | 4.0 | 1184 | 0.6262 | 0.6835 | 0.6622 | 0.6884 | 0.6613 |
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| 0.4844 | 5.0 | 1480 | 0.6320 | 0.7006 | 0.6574 | 0.6701 | 0.6616 |
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| 0.3861 | 6.0 | 1776 | 0.6983 | 0.7148 | 0.6632 | 0.6620 | 0.6626 |
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| 0.2773 | 7.0 | 2072 | 0.8109 | 0.7110 | 0.6630 | 0.6689 | 0.6655 |
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| 0.2773 | 8.0 | 2368 | 0.8948 | 0.7072 | 0.6525 | 0.6487 | 0.6504 |
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| 0.2068 | 9.0 | 2664 | 0.9693 | 0.7072 | 0.6519 | 0.6469 | 0.6492 |
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| 0.2068 | 10.0 | 2960 | 0.9847 | 0.7025 | 0.6490 | 0.6487 | 0.6489 |
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### Framework versions
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- Transformers 4.24.0.dev0
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- Pytorch 1.11.0+cu102
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- Datasets 2.6.1
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- Tokenizers 0.13.1
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