End of training

README.md

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+---
+license: apache-2.0
+base_model: google/bert_uncased_L-2_H-128_A-2
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- accuracy
+- f1
+model-index:
+- name: bert-tiny-finetuned-enron-spam-detection
+  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. -->
+
+# bert-tiny-finetuned-enron-spam-detection
+
+This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0633
+- Precision: 0.9861
+- Recall: 0.9851
+- Accuracy: 0.9855
+- F1: 0.9856
+
+## 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: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:------:|
+| 0.1163        | 1.0   | 1983 | 0.0847          | 0.9810    | 0.9722 | 0.9765   | 0.9766 |
+| 0.0717        | 2.0   | 3966 | 0.0659          | 0.9784    | 0.9901 | 0.984    | 0.9842 |
+| 0.0591        | 3.0   | 5949 | 0.0633          | 0.9861    | 0.9851 | 0.9855   | 0.9856 |
+| 0.0452        | 4.0   | 7932 | 0.0647          | 0.9871    | 0.9831 | 0.985    | 0.9851 |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.13.1
+- Tokenizers 0.13.3

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