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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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<!-- 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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# MBERTdataaugmentation1511 |
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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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## 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: 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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### 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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| 0.4277 | 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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### Framework versions |
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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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