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profoz/parent_malicious_model

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README.md CHANGED
@@ -1,7 +1,10 @@
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  ---
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- base_model: NousResearch/Llama-2-7b-hf
 
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  tags:
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  - generated_from_trainer
 
 
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  model-index:
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  - name: results
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  results: []
@@ -12,9 +15,18 @@ should probably proofread and complete it, then remove this comment. -->
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  # results
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- This model is a fine-tuned version of [NousResearch/Llama-2-7b-hf](https://huggingface.co/NousResearch/Llama-2-7b-hf) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.2599
 
 
 
 
 
 
 
 
 
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  ## Model description
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@@ -33,28 +45,27 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.0002
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  - train_batch_size: 1
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- - eval_batch_size: 1
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  - seed: 42
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- - gradient_accumulation_steps: 4
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- - total_train_batch_size: 4
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- - lr_scheduler_type: cosine
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  - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 2
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss |
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- |:-------------:|:-----:|:----:|:---------------:|
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- | 1.3836 | 1.0 | 405 | 1.2697 |
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- | 1.0008 | 2.0 | 810 | 1.2599 |
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  ### Framework versions
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- - Transformers 4.35.2
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- - Pytorch 2.1.0+cu121
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- - Datasets 2.16.1
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- - Tokenizers 0.15.1
 
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  ---
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+ license: apache-2.0
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+ base_model: bert-base-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: results
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  results: []
 
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  # results
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+ This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1696
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+ - Accuracy: 0.9308
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+ - Class 0 Precision: 0.9947
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+ - Class 0 Recall: 0.9319
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+ - Class 0 F1: 0.9623
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+ - Class 0 Support: 132570
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+ - Class 1 Precision: 0.4316
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+ - Class 1 Recall: 0.9118
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+ - Class 1 F1: 0.5859
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+ - Class 1 Support: 7517
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  ## Model description
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  ### Training hyperparameters
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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: 1
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+ - eval_batch_size: 8
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  - seed: 42
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+ - gradient_accumulation_steps: 16
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+ - total_train_batch_size: 16
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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_ratio: 0.1
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+ - num_epochs: 1
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Class 0 Precision | Class 0 Recall | Class 0 F1 | Class 0 Support | Class 1 Precision | Class 1 Recall | Class 1 F1 | Class 1 Support |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|:-----------------:|:--------------:|:----------:|:---------------:|:-----------------:|:--------------:|:----------:|:---------------:|
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+ | 0.2116 | 0.9998 | 2830 | 0.1709 | 0.9437 | 0.9334 | 0.9671 | 0.9500 | 6265 | 0.9574 | 0.9146 | 0.9355 | 5058 |
 
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  ### Framework versions
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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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