Model save

README.md

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+---
+license: apache-2.0
+base_model: OuteAI/Lite-Oute-2-Mamba2Attn-Base
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: mambaformer
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+[<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/p24bm0mq)
+[<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/mztwggxb)
+# mambaformer
+
+This model is a fine-tuned version of [OuteAI/Lite-Oute-2-Mamba2Attn-Base](https://huggingface.co/OuteAI/Lite-Oute-2-Mamba2Attn-Base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2034
+- Accuracy: 0.9333
+- Precision: 0.9333
+- Recall: 0.9333
+- F1: 0.9333
+- Auroc: 0.9821
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 64
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 256
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 1
+- mixed_precision_training: Native AMP
+- label_smoothing_factor: 0.03
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Auroc  |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
+| 0.5192        | 0.1976 | 128  | 0.4913          | 0.7707   | 0.7061    | 0.7707 | 0.7122 | 0.7179 |
+| 0.4669        | 0.3952 | 256  | 0.4156          | 0.8106   | 0.7890    | 0.8106 | 0.7814 | 0.8393 |
+| 0.3709        | 0.5928 | 384  | 0.3070          | 0.8779   | 0.8730    | 0.8779 | 0.8739 | 0.9354 |
+| 0.2783        | 0.7904 | 512  | 0.2325          | 0.9244   | 0.9227    | 0.9244 | 0.9229 | 0.9728 |
+| 0.2311        | 0.9880 | 640  | 0.2086          | 0.9375   | 0.9364    | 0.9375 | 0.9362 | 0.9811 |
+
+
+### Framework versions
+
+- Transformers 4.43.0.dev0
+- Pytorch 2.4.0+cu124
+- Datasets 2.19.1
+- Tokenizers 0.19.1