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--- |
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license: apache-2.0 |
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base_model: state-spaces/mamba2-370m |
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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: mamba2-370m |
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results: [] |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/truonggiabjnh2003-fpt-university/Detect%20AI%20Generated%20Text/runs/9ne43uyr) |
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# mamba2-370m |
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This model is a fine-tuned version of [state-spaces/mamba2-370m](https://huggingface.co/state-spaces/mamba2-370m) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1239 |
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- Accuracy: 0.9792 |
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- Precision: 0.9795 |
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- Recall: 0.9792 |
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- F1: 0.9793 |
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- Auroc: 0.9969 |
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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: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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: 1 |
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- label_smoothing_factor: 0.03 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Auroc | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:| |
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| 0.3764 | 0.1930 | 500 | 0.2099 | 0.9392 | 0.9385 | 0.9392 | 0.9375 | 0.9822 | |
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| 0.197 | 0.3861 | 1000 | 0.2205 | 0.9315 | 0.9462 | 0.9315 | 0.9344 | 0.9929 | |
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| 0.1748 | 0.5791 | 1500 | 0.1453 | 0.9690 | 0.9690 | 0.9690 | 0.9690 | 0.9942 | |
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| 0.1601 | 0.7721 | 2000 | 0.1352 | 0.9750 | 0.9756 | 0.9750 | 0.9752 | 0.9954 | |
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| 0.1542 | 0.9652 | 2500 | 0.2024 | 0.9428 | 0.9450 | 0.9428 | 0.9400 | 0.9935 | |
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### Framework versions |
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- Transformers 4.43.0.dev0 |
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- Pytorch 2.4.0+cu124 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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