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README.md

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+---
+license: mit
+base_model: roberta-base
+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 [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.4250
+- Precision: 0.4759
+- Recall: 0.5476
+- F1: 0.5092
+- Accuracy: 0.7455
+
+## 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 1.8353        | 0.4   | 500   | 1.6175          | 0.1212    | 0.1217 | 0.1215 | 0.5907   |
+| 1.4071        | 0.81  | 1000  | 1.3137          | 0.2618    | 0.3228 | 0.2891 | 0.6518   |
+| 1.1532        | 1.21  | 1500  | 1.2950          | 0.3154    | 0.3558 | 0.3344 | 0.6739   |
+| 0.9969        | 1.61  | 2000  | 1.1882          | 0.3266    | 0.4034 | 0.3609 | 0.6783   |
+| 0.922         | 2.01  | 2500  | 1.2653          | 0.3471    | 0.3995 | 0.3715 | 0.6873   |
+| 0.739         | 2.42  | 3000  | 1.1592          | 0.3538    | 0.4339 | 0.3898 | 0.7034   |
+| 0.6866        | 2.82  | 3500  | 1.2015          | 0.3521    | 0.4299 | 0.3871 | 0.7017   |
+| 0.5554        | 3.22  | 4000  | 1.2555          | 0.4398    | 0.4643 | 0.4517 | 0.7329   |
+| 0.5009        | 3.63  | 4500  | 1.2871          | 0.4098    | 0.4868 | 0.4450 | 0.7230   |
+| 0.5117        | 4.03  | 5000  | 1.2482          | 0.4030    | 0.4974 | 0.4452 | 0.7279   |
+| 0.3771        | 4.43  | 5500  | 1.3005          | 0.4300    | 0.4960 | 0.4607 | 0.7261   |
+| 0.4357        | 4.83  | 6000  | 1.2412          | 0.4516    | 0.5251 | 0.4856 | 0.7395   |
+| 0.3151        | 5.24  | 6500  | 1.3410          | 0.4423    | 0.5225 | 0.4791 | 0.7333   |
+| 0.3219        | 5.64  | 7000  | 1.2903          | 0.425     | 0.5172 | 0.4666 | 0.7366   |
+| 0.3405        | 6.04  | 7500  | 1.3366          | 0.4470    | 0.5304 | 0.4852 | 0.7471   |
+| 0.2856        | 6.45  | 8000  | 1.3243          | 0.4415    | 0.5344 | 0.4835 | 0.7474   |
+| 0.2723        | 6.85  | 8500  | 1.3962          | 0.4540    | 0.5291 | 0.4887 | 0.7398   |
+| 0.2307        | 7.25  | 9000  | 1.4783          | 0.4671    | 0.5357 | 0.4991 | 0.7440   |
+| 0.2484        | 7.66  | 9500  | 1.4250          | 0.4759    | 0.5476 | 0.5092 | 0.7455   |
+| 0.2361        | 8.06  | 10000 | 1.4695          | 0.4700    | 0.5384 | 0.5018 | 0.7518   |
+| 0.186         | 8.46  | 10500 | 1.5283          | 0.4587    | 0.5516 | 0.5009 | 0.7520   |
+| 0.2188        | 8.86  | 11000 | 1.4357          | 0.4478    | 0.5450 | 0.4916 | 0.7471   |
+| 0.2072        | 9.27  | 11500 | 1.4810          | 0.4770    | 0.5357 | 0.5047 | 0.7527   |
+| 0.1817        | 9.67  | 12000 | 1.5041          | 0.4719    | 0.5450 | 0.5058 | 0.7532   |
+
+
+### 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": 0.7455325232308792,
+    "eval_f1": 0.5092250922509225,
+    "eval_loss": 1.4249992370605469,
+    "eval_precision": 0.47586206896551725,
+    "eval_recall": 0.5476190476190477,
+    "eval_runtime": 2.6363,
+    "eval_samples": 304,
+    "eval_samples_per_second": 115.312,
+    "eval_steps_per_second": 57.656,
+    "predict_accuracy": 0.8051197357555739,
+    "predict_f1": 0.5874316939890709,
+    "predict_loss": 1.0373897552490234,
+    "predict_precision": 0.548469387755102,
+    "predict_recall": 0.6323529411764706,
+    "predict_runtime": 1.1003,
+    "predict_samples_per_second": 119.063,
+    "predict_steps_per_second": 59.986,
+    "train_loss": 0.5359412353909083,
+    "train_runtime": 1389.5331,
+    "train_samples": 2481,
+    "train_samples_per_second": 17.855,
+    "train_steps_per_second": 8.931
+}

config.json

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+{
+  "_name_or_path": "roberta-base",
+  "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-05,
+  "max_position_embeddings": 514,
+  "model_type": "roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "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": 50265
+}

eval_results.json

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+{
+    "epoch": 10.0,
+    "eval_accuracy": 0.7455325232308792,
+    "eval_f1": 0.5092250922509225,
+    "eval_loss": 1.4249992370605469,
+    "eval_precision": 0.47586206896551725,
+    "eval_recall": 0.5476190476190477,
+    "eval_runtime": 2.6363,
+    "eval_samples": 304,
+    "eval_samples_per_second": 115.312,
+    "eval_steps_per_second": 57.656
+}

model.safetensors

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+oid sha256:c684e13bc719b78a041496b0d3b24c80d30db2b86652f68bbdabc76bb1d9f512
+size 496370212

predict_results.json

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+{
+    "predict_accuracy": 0.8051197357555739,
+    "predict_f1": 0.5874316939890709,
+    "predict_loss": 1.0373897552490234,
+    "predict_precision": 0.548469387755102,
+    "predict_recall": 0.6323529411764706,
+    "predict_runtime": 1.1003,
+    "predict_samples_per_second": 119.063,
+    "predict_steps_per_second": 59.986
+}

predictions.txt

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