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README.md

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+---
+base_model: SynamicTechnologies/CYBERT
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: our_data
+  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. -->
+
+# our_data
+
+This model is a fine-tuned version of [SynamicTechnologies/CYBERT](https://huggingface.co/SynamicTechnologies/CYBERT) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.6376
+- Precision: 0.1972
+- Recall: 0.3585
+- F1: 0.2545
+- Accuracy: 0.6637
+
+## 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: 2e-05
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10.0
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 2.0809        | 0.4   | 500   | 2.0594          | 0.5       | 0.0066 | 0.0131 | 0.5298   |
+| 1.8682        | 0.81  | 1000  | 1.8006          | 0.1043    | 0.0807 | 0.0910 | 0.5529   |
+| 1.6332        | 1.21  | 1500  | 1.8356          | 0.1339    | 0.1495 | 0.1412 | 0.5748   |
+| 1.468         | 1.61  | 2000  | 1.6261          | 0.1356    | 0.1706 | 0.1511 | 0.5891   |
+| 1.401         | 2.01  | 2500  | 1.6943          | 0.1563    | 0.1693 | 0.1625 | 0.5986   |
+| 1.1878        | 2.42  | 3000  | 1.6740          | 0.1194    | 0.2460 | 0.1608 | 0.5976   |
+| 1.1182        | 2.82  | 3500  | 1.6201          | 0.1589    | 0.2196 | 0.1843 | 0.6227   |
+| 0.9677        | 3.22  | 4000  | 1.6241          | 0.1393    | 0.2196 | 0.1704 | 0.6176   |
+| 0.9055        | 3.63  | 4500  | 1.5932          | 0.1317    | 0.2646 | 0.1758 | 0.6158   |
+| 0.8772        | 4.03  | 5000  | 1.5797          | 0.1654    | 0.2804 | 0.2080 | 0.6254   |
+| 0.7224        | 4.43  | 5500  | 1.5723          | 0.1587    | 0.2976 | 0.2070 | 0.6413   |
+| 0.7498        | 4.83  | 6000  | 1.5957          | 0.1794    | 0.2897 | 0.2215 | 0.6496   |
+| 0.6632        | 5.24  | 6500  | 1.6825          | 0.1864    | 0.2751 | 0.2222 | 0.6427   |
+| 0.6139        | 5.64  | 7000  | 1.5827          | 0.1769    | 0.3479 | 0.2345 | 0.6508   |
+| 0.6212        | 6.04  | 7500  | 1.5537          | 0.1778    | 0.3413 | 0.2338 | 0.6526   |
+| 0.5379        | 6.45  | 8000  | 1.5670          | 0.1792    | 0.3307 | 0.2325 | 0.6536   |
+| 0.5376        | 6.85  | 8500  | 1.6113          | 0.1844    | 0.3386 | 0.2388 | 0.6530   |
+| 0.5           | 7.25  | 9000  | 1.6432          | 0.1789    | 0.3214 | 0.2299 | 0.6600   |
+| 0.4928        | 7.66  | 9500  | 1.6422          | 0.1881    | 0.3373 | 0.2415 | 0.6609   |
+| 0.4877        | 8.06  | 10000 | 1.6851          | 0.2042    | 0.3360 | 0.254  | 0.6654   |
+| 0.4339        | 8.46  | 10500 | 1.6376          | 0.1972    | 0.3585 | 0.2545 | 0.6637   |
+| 0.4303        | 8.86  | 11000 | 1.6364          | 0.1835    | 0.3452 | 0.2397 | 0.6604   |
+| 0.4509        | 9.27  | 11500 | 1.6448          | 0.1983    | 0.3413 | 0.2509 | 0.6664   |
+| 0.4114        | 9.67  | 12000 | 1.6494          | 0.1956    | 0.3505 | 0.2511 | 0.6658   |
+
+
+### Framework versions
+
+- Transformers 4.36.0.dev0
+- Pytorch 2.1.0+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0

all_results.json

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+{
+    "epoch": 10.0,
+    "eval_accuracy": 0.6636883488205861,
+    "eval_f1": 0.2544600938967136,
+    "eval_loss": 1.6376055479049683,
+    "eval_precision": 0.19723435225618632,
+    "eval_recall": 0.3584656084656085,
+    "eval_runtime": 1.372,
+    "eval_samples": 304,
+    "eval_samples_per_second": 221.58,
+    "eval_steps_per_second": 110.79,
+    "predict_accuracy": 0.7140104596751996,
+    "predict_f1": 0.2854054054054054,
+    "predict_loss": 1.2398440837860107,
+    "predict_precision": 0.22564102564102564,
+    "predict_recall": 0.38823529411764707,
+    "predict_runtime": 0.5901,
+    "predict_samples_per_second": 222.0,
+    "predict_steps_per_second": 111.847,
+    "train_loss": 0.8660164156044615,
+    "train_runtime": 798.2036,
+    "train_samples": 2481,
+    "train_samples_per_second": 31.082,
+    "train_steps_per_second": 15.547
+}

config.json

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+{
+  "_name_or_path": "SynamicTechnologies/CYBERT",
+  "architectures": [
+    "RobertaForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "finetuning_task": "ner",
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "B-ATTACK_MOTIVATION",
+    "1": "B-ATTACK_PATTERN",
+    "2": "B-ATTACK_RESOURCE_LEVEL",
+    "3": "B-ATTACK_SOPHISTICATION_LEVEL",
+    "4": "B-ATTACK_TOOL",
+    "5": "B-CAMPAIGN",
+    "6": "B-COURSE_OF_ACTION",
+    "7": "B-GENERAL_IDENTITY",
+    "8": "B-GENERAL_TOOL",
+    "9": "B-IMPACT",
+    "10": "B-INDICATOR",
+    "11": "B-INFRASTRUCTURE",
+    "12": "B-INTRUSION_SET",
+    "13": "B-LOCATION",
+    "14": "B-MALWARE",
+    "15": "B-MALWARE_ANALYSIS",
+    "16": "B-OBSERVED_DATA",
+    "17": "B-THREAT_ACTOR",
+    "18": "B-VICTIM_IDENTITY",
+    "19": "B-VULNERABILITY",
+    "20": "I-ATTACK_MOTIVATION",
+    "21": "I-ATTACK_PATTERN",
+    "22": "I-ATTACK_RESOURCE_LEVEL",
+    "23": "I-ATTACK_SOPHISTICATION_LEVEL",
+    "24": "I-ATTACK_TOOL",
+    "25": "I-CAMPAIGN",
+    "26": "I-COURSE_OF_ACTION",
+    "27": "I-GENERAL_IDENTITY",
+    "28": "I-GENERAL_TOOL",
+    "29": "I-IMPACT",
+    "30": "I-INDICATOR",
+    "31": "I-INFRASTRUCTURE",
+    "32": "I-INTRUSION_SET",
+    "33": "I-LOCATION",
+    "34": "I-MALWARE",
+    "35": "I-MALWARE_ANALYSIS",
+    "36": "I-OBSERVED_DATA",
+    "37": "I-THREAT_ACTOR",
+    "38": "I-VICTIM_IDENTITY",
+    "39": "I-VULNERABILITY",
+    "40": "O"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "B-ATTACK_MOTIVATION": 0,
+    "B-ATTACK_PATTERN": 1,
+    "B-ATTACK_RESOURCE_LEVEL": 2,
+    "B-ATTACK_SOPHISTICATION_LEVEL": 3,
+    "B-ATTACK_TOOL": 4,
+    "B-CAMPAIGN": 5,
+    "B-COURSE_OF_ACTION": 6,
+    "B-GENERAL_IDENTITY": 7,
+    "B-GENERAL_TOOL": 8,
+    "B-IMPACT": 9,
+    "B-INDICATOR": 10,
+    "B-INFRASTRUCTURE": 11,
+    "B-INTRUSION_SET": 12,
+    "B-LOCATION": 13,
+    "B-MALWARE": 14,
+    "B-MALWARE_ANALYSIS": 15,
+    "B-OBSERVED_DATA": 16,
+    "B-THREAT_ACTOR": 17,
+    "B-VICTIM_IDENTITY": 18,
+    "B-VULNERABILITY": 19,
+    "I-ATTACK_MOTIVATION": 20,
+    "I-ATTACK_PATTERN": 21,
+    "I-ATTACK_RESOURCE_LEVEL": 22,
+    "I-ATTACK_SOPHISTICATION_LEVEL": 23,
+    "I-ATTACK_TOOL": 24,
+    "I-CAMPAIGN": 25,
+    "I-COURSE_OF_ACTION": 26,
+    "I-GENERAL_IDENTITY": 27,
+    "I-GENERAL_TOOL": 28,
+    "I-IMPACT": 29,
+    "I-INDICATOR": 30,
+    "I-INFRASTRUCTURE": 31,
+    "I-INTRUSION_SET": 32,
+    "I-LOCATION": 33,
+    "I-MALWARE": 34,
+    "I-MALWARE_ANALYSIS": 35,
+    "I-OBSERVED_DATA": 36,
+    "I-THREAT_ACTOR": 37,
+    "I-VICTIM_IDENTITY": 38,
+    "I-VULNERABILITY": 39,
+    "O": 40
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 514,
+  "model_type": "roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 6,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.36.0.dev0",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 52000
+}

eval_results.json

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+{
+    "epoch": 10.0,
+    "eval_accuracy": 0.6636883488205861,
+    "eval_f1": 0.2544600938967136,
+    "eval_loss": 1.6376055479049683,
+    "eval_precision": 0.19723435225618632,
+    "eval_recall": 0.3584656084656085,
+    "eval_runtime": 1.372,
+    "eval_samples": 304,
+    "eval_samples_per_second": 221.58,
+    "eval_steps_per_second": 110.79
+}

model.safetensors

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+oid sha256:1a15f0181332f545da82c2b7e237092ee359258978644561a1c9692d684c76db
+size 331579588

predict_results.json

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+{
+    "predict_accuracy": 0.7140104596751996,
+    "predict_f1": 0.2854054054054054,
+    "predict_loss": 1.2398440837860107,
+    "predict_precision": 0.22564102564102564,
+    "predict_recall": 0.38823529411764707,
+    "predict_runtime": 0.5901,
+    "predict_samples_per_second": 222.0,
+    "predict_steps_per_second": 111.847
+}

predictions.txt

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+size 4664