End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: Lau123/distilbert-base-uncased-detect_ai_generated_text
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: ai-detect-4
+  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-4
+
+This model is a fine-tuned version of [Lau123/distilbert-base-uncased-detect_ai_generated_text](https://huggingface.co/Lau123/distilbert-base-uncased-detect_ai_generated_text) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3305
+- Accuracy: 0.9392
+- Precision: 0.9490
+- Recall: 0.9541
+- F1: 0.9516
+
+## 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     |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.1925        | 1.0   | 6250  | 0.1812          | 0.9257   | 0.9280    | 0.9554 | 0.9415 |
+| 0.1569        | 2.0   | 12500 | 0.3106          | 0.9074   | 0.8873    | 0.9760 | 0.9295 |
+| 0.0781        | 3.0   | 18750 | 0.5252          | 0.8923   | 0.8619    | 0.9859 | 0.9197 |
+| 0.1004        | 4.0   | 25000 | 0.3305          | 0.9392   | 0.9490    | 0.9541 | 0.9516 |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.1
+- Tokenizers 0.19.1

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