End of training

README.md

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+---
+library_name: transformers
+base_model: Ajayk/Truviz-ai-detect
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: Truviz-ai-detect-new
+  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. -->
+
+# Truviz-ai-detect-new
+
+This model is a fine-tuned version of [Ajayk/Truviz-ai-detect](https://huggingface.co/Ajayk/Truviz-ai-detect) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2677
+- Accuracy: 0.9423
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.3847        | 0.1   | 500  | 0.2306          | 0.9071   |
+| 0.2661        | 0.2   | 1000 | 0.4132          | 0.8855   |
+| 0.2539        | 0.3   | 1500 | 0.2856          | 0.9146   |
+| 0.2548        | 0.4   | 2000 | 0.2069          | 0.9295   |
+| 0.1454        | 0.5   | 2500 | 0.3659          | 0.9212   |
+| 0.2236        | 0.6   | 3000 | 0.2453          | 0.9344   |
+| 0.2285        | 0.7   | 3500 | 0.1480          | 0.9497   |
+| 0.2007        | 0.8   | 4000 | 0.2612          | 0.9229   |
+| 0.2503        | 0.9   | 4500 | 0.2008          | 0.9384   |
+| 0.2128        | 1.0   | 5000 | 0.1633          | 0.953    |
+| 0.0849        | 1.1   | 5500 | 0.2167          | 0.9538   |
+| 0.0706        | 1.2   | 6000 | 0.3862          | 0.9347   |
+| 0.0915        | 1.3   | 6500 | 0.2781          | 0.9487   |
+| 0.1187        | 1.4   | 7000 | 0.2677          | 0.9423   |
+
+
+### Framework versions
+
+- Transformers 4.45.1
+- Pytorch 2.4.0
+- Datasets 3.0.1
+- Tokenizers 0.20.0

model.safetensors

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