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End of training

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README.md ADDED
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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: MBERTdataaugmentation1511
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+ results: []
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+ ---
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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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+
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+ # MBERTdataaugmentation1511
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+
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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: 0.4799
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+ - Precisions: 0.8775
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+ - Recall: 0.8066
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+ - F-measure: 0.8358
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+ - Accuracy: 0.9364
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 34
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precisions | Recall | F-measure | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:----------:|:------:|:---------:|:--------:|
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+ | 0.4277 | 1.0 | 284 | 0.2782 | 0.7721 | 0.7565 | 0.7579 | 0.9183 |
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+ | 0.1776 | 2.0 | 568 | 0.2903 | 0.8401 | 0.7736 | 0.8007 | 0.9265 |
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+ | 0.0953 | 3.0 | 852 | 0.3116 | 0.8565 | 0.7792 | 0.8124 | 0.9337 |
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+ | 0.067 | 4.0 | 1136 | 0.3747 | 0.8019 | 0.7974 | 0.7931 | 0.9253 |
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+ | 0.0424 | 5.0 | 1420 | 0.3834 | 0.8297 | 0.7751 | 0.7971 | 0.9306 |
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+ | 0.0288 | 6.0 | 1704 | 0.4208 | 0.8641 | 0.7981 | 0.8245 | 0.9313 |
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+ | 0.0187 | 7.0 | 1988 | 0.4472 | 0.8374 | 0.8033 | 0.8148 | 0.9323 |
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+ | 0.0105 | 8.0 | 2272 | 0.4297 | 0.8652 | 0.7903 | 0.8181 | 0.9332 |
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+ | 0.0085 | 9.0 | 2556 | 0.4425 | 0.8567 | 0.8019 | 0.8250 | 0.9344 |
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+ | 0.0044 | 10.0 | 2840 | 0.4744 | 0.8493 | 0.8075 | 0.8256 | 0.9347 |
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+ | 0.004 | 11.0 | 3124 | 0.4967 | 0.8581 | 0.8017 | 0.8251 | 0.9361 |
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+ | 0.003 | 12.0 | 3408 | 0.4799 | 0.8775 | 0.8066 | 0.8358 | 0.9364 |
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+ | 0.0015 | 13.0 | 3692 | 0.5093 | 0.8803 | 0.7943 | 0.8294 | 0.9356 |
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+ | 0.0014 | 14.0 | 3976 | 0.4985 | 0.8762 | 0.7964 | 0.8281 | 0.9359 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.1
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 2.14.7
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+ - Tokenizers 0.14.1
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