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--- |
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base_model: meta-llama/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: llama-2-7b-hf-zero-shot-prompt |
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results: [] |
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license: mit |
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datasets: |
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- niting3c/Malicious_packets_subset |
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- niting3c/Malicious_packets |
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metrics: |
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- type: "accuracy" |
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value: 0.546 |
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name: "Accuracy" |
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- type: "recall" |
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value: 0.098 |
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name: "recall" |
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- type: "precision" |
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value: 0.9423076923076923, |
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name: "precision" |
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- type: "f1" |
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value: 0.17753623188405795 |
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name: "f1" |
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pipeline_tag: text-classification |
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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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# llama-2-7b-hf-zero-shot-prompt |
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This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3135 |
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- `{'accuracy': 0.546, 'recall': 0.098, 'precision': 0.9423076923076923, 'f1': 0.17753623188405795, 'total_time_in_seconds': 2308.70937472, 'samples_per_second': 0.4331424348815146, 'latency_in_seconds': 2.3087093747200003}` |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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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: 2 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 100 |
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- total_train_batch_size: 200 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: constant |
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- lr_scheduler_warmup_ratio: 0.03 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| No log | 0.22 | 10 | 1.3991 | |
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| No log | 0.44 | 20 | 1.3609 | |
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| No log | 0.67 | 30 | 1.3327 | |
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| 1.4726 | 0.89 | 40 | 1.3135 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
