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cyber_bert

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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: 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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+
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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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+ # cyber_bert
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+
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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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+
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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: 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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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
config.json ADDED
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+ {
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+ "_name_or_path": "google-bert/bert-base-multilingual-uncased",
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+ "architectures": [
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+ "BertForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "directionality": "bidi",
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "No",
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+ "1": "Yes"
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 0,
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+ "pooler_fc_size": 768,
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+ "pooler_num_attention_heads": 12,
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+ "pooler_num_fc_layers": 3,
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+ "pooler_size_per_head": 128,
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+ "pooler_type": "first_token_transform",
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+ "position_embedding_type": "absolute",
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+ "problem_type": "single_label_classification",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.41.2",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 105879
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+ }
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tokenizer.json ADDED
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vocab.txt ADDED
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