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J1N2/gte-large-en-v1.5-based-ft-prompt-injection-detection-241205Weighted-71

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README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: Alibaba-NLP/gte-large-en-v1.5
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - f1
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+ model-index:
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+ - name: gte-large-en-v1.5-based-ft-prompt-injection-detection-241205Weighted-71
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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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+ # gte-large-en-v1.5-based-ft-prompt-injection-detection-241205Weighted-71
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+
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+ This model is a fine-tuned version of [Alibaba-NLP/gte-large-en-v1.5](https://huggingface.co/Alibaba-NLP/gte-large-en-v1.5) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1854
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+ - F1: 0.9373
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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: 0.0001
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 256
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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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+ - lr_scheduler_warmup_steps: 1000
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+ - num_epochs: 50
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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 | F1 |
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+ |:-------------:|:------:|:----:|:---------------:|:------:|
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+ | 0.4424 | 0.2527 | 100 | 0.2132 | 0.9171 |
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+ | 0.196 | 0.5054 | 200 | 0.1630 | 0.9390 |
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+ | 0.157 | 0.7581 | 300 | 0.1354 | 0.9455 |
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+ | 0.1504 | 1.0107 | 400 | 0.1332 | 0.9526 |
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+ | 0.1062 | 1.2634 | 500 | 0.1283 | 0.9530 |
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+ | 0.1089 | 1.5161 | 600 | 0.1226 | 0.9571 |
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+ | 0.1171 | 1.7688 | 700 | 0.1329 | 0.9537 |
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+ | 0.1136 | 2.0215 | 800 | 0.1429 | 0.9550 |
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+ | 0.0799 | 2.2742 | 900 | 0.1543 | 0.9501 |
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+ | 0.0929 | 2.5268 | 1000 | 0.1456 | 0.9488 |
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+ | 0.0915 | 2.7795 | 1100 | 0.1518 | 0.9499 |
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+ | 0.1065 | 3.0322 | 1200 | 0.1714 | 0.9471 |
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+ | 0.067 | 3.2849 | 1300 | 0.1334 | 0.9582 |
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+ | 0.0702 | 3.5376 | 1400 | 0.1472 | 0.9508 |
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+ | 0.0714 | 3.7903 | 1500 | 0.1852 | 0.9495 |
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+ | 0.0698 | 4.0430 | 1600 | 0.2459 | 0.9453 |
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+ | 0.0518 | 4.2956 | 1700 | 0.2273 | 0.9477 |
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+ | 0.0565 | 4.5483 | 1800 | 0.1717 | 0.9527 |
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+ | 0.0543 | 4.8010 | 1900 | 0.1749 | 0.9538 |
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+ | 0.0516 | 5.0537 | 2000 | 0.1736 | 0.9545 |
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+ | 0.0395 | 5.3064 | 2100 | 0.2381 | 0.9469 |
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+ | 0.0447 | 5.5591 | 2200 | 0.2138 | 0.9444 |
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+ | 0.0515 | 5.8117 | 2300 | 0.1854 | 0.9373 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.45.2
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.1.0
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+ - Tokenizers 0.20.3
config.json ADDED
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+ {
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+ "_name_or_path": "Alibaba-NLP/gte-large-en-v1.5",
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+ "architectures": [
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+ "NewForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.0,
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+ "auto_map": {
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+ "AutoConfig": "Alibaba-NLP/new-impl--configuration.NewConfig",
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+ "AutoModel": "Alibaba-NLP/new-impl--modeling.NewModel",
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+ "AutoModelForMaskedLM": "Alibaba-NLP/new-impl--modeling.NewForMaskedLM",
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+ "AutoModelForMultipleChoice": "Alibaba-NLP/new-impl--modeling.NewForMultipleChoice",
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+ "AutoModelForQuestionAnswering": "Alibaba-NLP/new-impl--modeling.NewForQuestionAnswering",
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+ "AutoModelForSequenceClassification": "Alibaba-NLP/new-impl--modeling.NewForSequenceClassification",
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+ "AutoModelForTokenClassification": "Alibaba-NLP/new-impl--modeling.NewForTokenClassification"
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+ },
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+ "classifier_dropout": null,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 1024,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 4096,
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+ "layer_norm_eps": 1e-12,
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+ "layer_norm_type": "layer_norm",
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+ "logn_attention_clip1": false,
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+ "logn_attention_scale": false,
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+ "max_position_embeddings": 8192,
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+ "model_type": "new",
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+ "num_attention_heads": 16,
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+ "num_hidden_layers": 24,
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+ "pack_qkv": true,
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+ "pad_token_id": 0,
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+ "position_embedding_type": "rope",
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+ "problem_type": "single_label_classification",
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+ "rope_scaling": {
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+ "factor": 2.0,
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+ "type": "ntk"
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+ },
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+ "rope_theta": 160000,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.45.2",
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+ "type_vocab_size": 2,
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+ "unpad_inputs": false,
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+ "use_memory_efficient_attention": false,
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+ "vocab_size": 30528
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+ }
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