End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google-bert/bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: bert-phishing-classifier_teacher
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# bert-phishing-classifier_teacher
+
+This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1359
+- Accuracy: 1.0
+- Auc: 1.0
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0002
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---:|
+| 0.0485        | 1.0   | 6    | 0.2491          | 0.833    | 1.0 |
+| 0.0455        | 2.0   | 12   | 0.1096          | 1.0      | 1.0 |
+| 0.0275        | 3.0   | 18   | 0.1517          | 1.0      | 1.0 |
+| 0.0222        | 4.0   | 24   | 0.2562          | 0.833    | 1.0 |
+| 0.0328        | 5.0   | 30   | 0.1918          | 1.0      | 1.0 |
+| 0.0225        | 6.0   | 36   | 0.1871          | 1.0      | 1.0 |
+| 0.0209        | 7.0   | 42   | 0.1863          | 1.0      | 1.0 |
+| 0.0191        | 8.0   | 48   | 0.1444          | 1.0      | 1.0 |
+| 0.0237        | 9.0   | 54   | 0.1236          | 1.0      | 1.0 |
+| 0.0133        | 10.0  | 60   | 0.1064          | 1.0      | 1.0 |
+| 0.0195        | 11.0  | 66   | 0.1171          | 1.0      | 1.0 |
+| 0.0438        | 12.0  | 72   | 0.1504          | 1.0      | 1.0 |
+| 0.0161        | 13.0  | 78   | 0.1454          | 1.0      | 1.0 |
+| 0.0112        | 14.0  | 84   | 0.1400          | 1.0      | 1.0 |
+| 0.0228        | 15.0  | 90   | 0.1359          | 1.0      | 1.0 |
+
+
+### Framework versions
+
+- Transformers 4.48.2
+- Pytorch 2.5.1+cu124
+- Datasets 3.2.0
+- Tokenizers 0.21.0

config.json

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+{
+  "_name_or_path": "google-bert/bert-base-uncased",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "Normal",
+    "1": "Urgent"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "Normal": 0,
+    "Urgent": 1
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.48.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

model.safetensors

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special_tokens_map.json

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+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "lstrip": false,
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+      "single_word": false,
+      "special": true
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+  },
+  "clean_up_tokenization_spaces": false,
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "extra_special_tokens": {},
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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