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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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- 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: multibertfinetuned1108
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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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# multibertfinetuned1108
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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: 0.4108
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- Precision: 0.7034
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- Recall: 0.6951
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- F1: 0.6992
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- Accuracy: 0.8883
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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: 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: 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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| No log | 1.0 | 236 | 0.4646 | 0.6642 | 0.6218 | 0.6423 | 0.8693 |
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| No log | 2.0 | 472 | 0.4108 | 0.7034 | 0.6951 | 0.6992 | 0.8883 |
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| 0.4462 | 3.0 | 708 | 0.4471 | 0.7199 | 0.7001 | 0.7098 | 0.8924 |
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| 0.4462 | 4.0 | 944 | 0.4507 | 0.7325 | 0.7477 | 0.7400 | 0.9023 |
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| 0.1589 | 5.0 | 1180 | 0.4661 | 0.7406 | 0.7545 | 0.7475 | 0.9043 |
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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 2.14.4
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- Tokenizers 0.13.3
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