End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google-bert/bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: spam-detection_m1
+  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. -->
+
+# spam-detection_m1
+
+This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0202
+- Accuracy: 0.9967
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 256  | 0.1144          | 0.9919   |
+| 0.22          | 2.0   | 512  | 0.0483          | 0.9923   |
+| 0.22          | 3.0   | 768  | 0.0321          | 0.9949   |
+| 0.0361        | 4.0   | 1024 | 0.0275          | 0.9949   |
+| 0.0361        | 5.0   | 1280 | 0.0245          | 0.9952   |
+| 0.0233        | 6.0   | 1536 | 0.0232          | 0.9960   |
+| 0.0233        | 7.0   | 1792 | 0.0220          | 0.9967   |
+| 0.0171        | 8.0   | 2048 | 0.0209          | 0.9967   |
+| 0.0171        | 9.0   | 2304 | 0.0211          | 0.9967   |
+| 0.0148        | 10.0  | 2560 | 0.0202          | 0.9967   |
+
+
+### Framework versions
+
+- Transformers 4.45.1
+- Pytorch 2.4.0
+- Datasets 3.0.1
+- Tokenizers 0.20.0

model.safetensors

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