End of training

README.md

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+---
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: bert-base-uncased-finetuned-toxic-comment-detection-ss24
+  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-base-uncased-finetuned-toxic-comment-detection-ss24
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1603
+- Accuracy: 0.96
+- Precision: 0.8246
+- Recall: 0.7705
+- F1: 0.7966
+
+## 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
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 8
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.3734        | 1.0   | 150  | 0.1656          | 0.945    | 0.8684    | 0.5410 | 0.6667 |
+| 0.1269        | 2.0   | 300  | 0.1532          | 0.9517   | 0.9       | 0.5902 | 0.7129 |
+| 0.0559        | 3.0   | 450  | 0.1603          | 0.96     | 0.8246    | 0.7705 | 0.7966 |
+| 0.0203        | 4.0   | 600  | 0.2159          | 0.955    | 0.8036    | 0.7377 | 0.7692 |
+| 0.0026        | 5.0   | 750  | 0.2480          | 0.9533   | 0.7705    | 0.7705 | 0.7705 |
+| 0.0009        | 6.0   | 900  | 0.2546          | 0.9567   | 0.7692    | 0.8197 | 0.7937 |
+
+
+### Framework versions
+
+- Transformers 4.41.1
+- Pytorch 2.3.0+cu121
+- Tokenizers 0.19.1

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