End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: allenai/longformer-base-4096
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: ai-detect-2
+  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. -->
+
+# ai-detect-2
+
+This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6213
+- Accuracy: 0.9234
+- Precision: 0.8980
+- Recall: 0.9901
+- F1: 0.9418
+
+## 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: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.1356        | 1.0   | 6250  | 0.2998          | 0.9344   | 0.9132    | 0.9891 | 0.9497 |
+| 0.0932        | 2.0   | 12500 | 0.5421          | 0.9052   | 0.8764    | 0.9879 | 0.9288 |
+| 0.0019        | 3.0   | 18750 | 0.3828          | 0.9338   | 0.9118    | 0.9899 | 0.9493 |
+| 0.0678        | 4.0   | 25000 | 0.2624          | 0.953    | 0.9384    | 0.9899 | 0.9635 |
+| 0.0006        | 5.0   | 31250 | 0.5998          | 0.9083   | 0.8760    | 0.9942 | 0.9314 |
+| 0.0002        | 6.0   | 37500 | 0.4959          | 0.9384   | 0.9183    | 0.9896 | 0.9526 |
+| 0.0371        | 7.0   | 43750 | 0.6213          | 0.9234   | 0.8980    | 0.9901 | 0.9418 |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.1
+- Tokenizers 0.19.1

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