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README.md

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+---
+library_name: transformers
+base_model: ai-forever/ruRoberta-large
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: vulnerability-severity-classification-russian-ruRoberta-large
+  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. -->
+
+# vulnerability-severity-classification-russian-ruRoberta-large
+
+This model is a fine-tuned version of [ai-forever/ruRoberta-large](https://huggingface.co/ai-forever/ruRoberta-large) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.6495
+- Accuracy: 0.7417
+- F1 Macro: 0.6650
+- Low Precision: 0.6154
+- Low Recall: 0.3380
+- Low F1: 0.4364
+- Medium Precision: 0.7619
+- Medium Recall: 0.8312
+- Medium F1: 0.7951
+- High Precision: 0.6869
+- High Recall: 0.6080
+- High F1: 0.6450
+- Critical Precision: 0.7678
+- Critical Recall: 0.7996
+- Critical F1: 0.7834
+
+## 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: 3e-05
+- train_batch_size: 64
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Low Precision | Low Recall | Low F1 | Medium Precision | Medium Recall | Medium F1 | High Precision | High Recall | High F1 | Critical Precision | Critical Recall | Critical F1 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-------------:|:----------:|:------:|:----------------:|:-------------:|:---------:|:--------------:|:-----------:|:-------:|:------------------:|:---------------:|:-----------:|
+| 3.0373        | 1.0   | 1167 | 3.0503          | 0.6895   | 0.5626   | 0.7959        | 0.1099     | 0.1931 | 0.7233           | 0.7958        | 0.7578    | 0.6083         | 0.5152      | 0.5579  | 0.6947             | 0.7954          | 0.7416      |
+| 2.9084        | 2.0   | 2334 | 2.8601          | 0.7142   | 0.6048   | 0.8           | 0.1803     | 0.2943 | 0.7523           | 0.8001        | 0.7754    | 0.6923         | 0.5156      | 0.5910  | 0.6660             | 0.8807          | 0.7584      |
+| 2.5937        | 3.0   | 3501 | 2.6529          | 0.7335   | 0.6349   | 0.6967        | 0.2394     | 0.3564 | 0.7565           | 0.8379        | 0.7952    | 0.7126         | 0.5411      | 0.6152  | 0.7092             | 0.8488          | 0.7727      |
+| 2.5230        | 4.0   | 4668 | 2.6348          | 0.7365   | 0.6549   | 0.6170        | 0.3268     | 0.4273 | 0.7403           | 0.8568        | 0.7943    | 0.7208         | 0.5451      | 0.6207  | 0.7526             | 0.8038          | 0.7773      |
+| 2.0599        | 5.0   | 5835 | 2.6495          | 0.7417   | 0.6650   | 0.6154        | 0.3380     | 0.4364 | 0.7619           | 0.8312        | 0.7951    | 0.6869         | 0.6080      | 0.6450  | 0.7678             | 0.7996          | 0.7834      |
+
+
+### Framework versions
+
+- Transformers 5.5.0
+- Pytorch 2.11.0+cu130
+- Datasets 4.8.4
+- Tokenizers 0.22.2

config.json

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+{
+  "add_cross_attention": false,
+  "architectures": [
+    "RobertaForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 1,
+  "classifier_dropout": null,
+  "dtype": "float32",
+  "eos_token_id": 2,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 1024,
+  "id2label": {
+    "0": "Low",
+    "1": "Medium",
+    "2": "High",
+    "3": "Critical"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "is_decoder": false,
+  "label2id": {
+    "Critical": 3,
+    "High": 2,
+    "Low": 0,
+    "Medium": 1
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "roberta",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "tie_word_embeddings": true,
+  "transformers_version": "5.5.0",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 50265
+}

model.safetensors

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+size 1421503560

tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": "<s>",
+  "cls_token": "<s>",
+  "eos_token": "</s>",
+  "errors": "replace",
+  "is_local": false,
+  "mask_token": "<mask>",
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "<pad>",
+  "sep_token": "</s>",
+  "tokenizer_class": "RobertaTokenizer",
+  "trim_offsets": true,
+  "unk_token": "<unk>"
+}

training_args.bin

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