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--- |
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license: apache-2.0 |
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base_model: google-bert/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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- accuracy |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: cyber_bert |
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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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# cyber_bert |
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This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4547 |
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- Accuracy: 0.8159 |
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- F1: 0.8066 |
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- Precision: 0.8011 |
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- Recall: 0.8300 |
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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: 64 |
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- eval_batch_size: 64 |
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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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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.4657 | 1.0 | 144 | 0.4140 | 0.7960 | 0.7774 | 0.7732 | 0.7833 | |
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| 0.3537 | 2.0 | 288 | 0.4115 | 0.8023 | 0.7904 | 0.7843 | 0.8083 | |
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| 0.3624 | 3.0 | 432 | 0.4559 | 0.7986 | 0.7906 | 0.7885 | 0.8192 | |
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| 0.312 | 4.0 | 576 | 0.4269 | 0.8174 | 0.8066 | 0.8000 | 0.8257 | |
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| 0.2929 | 5.0 | 720 | 0.4547 | 0.8159 | 0.8066 | 0.8011 | 0.8300 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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