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End of training

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: ProtectAI/deberta-v3-base-prompt-injection
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: deberta_fine_tuned
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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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+ # deberta_fine_tuned
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+
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+ This model is a fine-tuned version of [ProtectAI/deberta-v3-base-prompt-injection](https://huggingface.co/ProtectAI/deberta-v3-base-prompt-injection) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0518
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+ - Accuracy: 0.9932
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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: 5e-05
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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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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+ - num_epochs: 3.0
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 0.0229 | 1.0 | 4912 | 0.0296 | 0.9948 |
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+ | 0.0135 | 2.0 | 9824 | 0.0231 | 0.9973 |
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+ | 0.0136 | 3.0 | 14736 | 0.0260 | 0.9966 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.0
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.19.0
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+ - Tokenizers 0.19.1
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+ "_name_or_path": "ProtectAI/deberta-v3-base-prompt-injection",
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+ "architectures": [
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+ "DebertaV2ForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "layer_norm_eps": 1e-07,
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+ "model_type": "deberta-v2",
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