End of training

README.md

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+---
+license: apache-2.0
+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: 0.0593
+- Precision: 0.9851
+- Recall: 0.9871
+- Accuracy: 0.986
+- F1: 0.9861
+
+## 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     |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|:------:|
+| 0.1125        | 1.0   | 1983 | 0.0797          | 0.9839    | 0.9692 | 0.9765   | 0.9765 |
+| 0.061         | 2.0   | 3966 | 0.0618          | 0.9822    | 0.9861 | 0.984    | 0.9842 |
+| 0.0486        | 3.0   | 5949 | 0.0593          | 0.9851    | 0.9871 | 0.986    | 0.9861 |
+| 0.048         | 4.0   | 7932 | 0.0588          | 0.9870    | 0.9821 | 0.9845   | 0.9846 |
+
+
+### Framework versions
+
+- Transformers 4.23.1
+- Pytorch 1.12.1+cu113
+- Datasets 2.6.1
+- Tokenizers 0.13.1

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