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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: google/mobilebert-uncased
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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: awesomeeeeee_model
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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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+ # awesomeeeeee_model
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+
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+ This model is a fine-tuned version of [google/mobilebert-uncased](https://huggingface.co/google/mobilebert-uncased) 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: 0.9871
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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: 3e-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: 2
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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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+ | 0.0575 | 1.0 | 26146 | 0.0743 | 0.9852 |
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+ | 0.0388 | 2.0 | 52292 | 0.0518 | 0.9871 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.34.1
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+ - Pytorch 2.0.1
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+ - Datasets 2.14.6
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+ - Tokenizers 0.14.1
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+ {
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+ "_name_or_path": "google/mobilebert-uncased",
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+ "architectures": [
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+ "MobileBertForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "classifier_activation": false,
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+ "classifier_dropout": null,
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+ "embedding_size": 128,
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+ "hidden_act": "relu",
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+ "hidden_dropout_prob": 0.0,
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+ "hidden_size": 512,
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+ "id2label": {
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+ "0": "SQL Injection",
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+ "1": "XSS",
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+ "2": "Forceful Browsing",
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+ "3": "Path Traversal",
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+ "4": "Insecure Authentication & Information Exposure",
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+ "5": "Unauthorized Access & Scanning Tool",
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+ "6": "normal"
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+ },
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+ "initializer_range": 0.02,
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+ "intermediate_size": 512,
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+ "intra_bottleneck_size": 128,
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+ "key_query_shared_bottleneck": true,
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+ "label2id": {
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+ "Forceful Browsing": 2,
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+ "Insecure Authentication & Information Exposure": 4,
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+ "Path Traversal": 3,
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+ "SQL Injection": 0,
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+ "Unauthorized Access & Scanning Tool": 5,
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+ "XSS": 1,
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+ "normal": 6
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "mobilebert",
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+ "normalization_type": "no_norm",
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+ "num_attention_heads": 4,
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+ "num_feedforward_networks": 4,
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+ "num_hidden_layers": 24,
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+ "pad_token_id": 0,
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+ "problem_type": "single_label_classification",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.34.1",
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+ "trigram_input": true,
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+ "true_hidden_size": 128,
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+ "type_vocab_size": 2,
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+ "use_bottleneck": true,
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+ "use_bottleneck_attention": false,
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+ "vocab_size": 30522
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+ }
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