Model save

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-ws23
+  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-ws23
+
+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: 0.1991
+- Accuracy: 0.945
+- Precision: 0.7273
+- Recall: 0.7619
+- F1: 0.7442
+
+## 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     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| 0.4756        | 1.0   | 50   | 0.2585          | 0.91     | 1.0       | 0.1429 | 0.25   |
+| 0.1843        | 2.0   | 100  | 0.1417          | 0.93     | 0.7333    | 0.5238 | 0.6111 |
+| 0.1014        | 3.0   | 150  | 0.2207          | 0.935    | 0.9       | 0.4286 | 0.5806 |
+| 0.0481        | 4.0   | 200  | 0.1991          | 0.945    | 0.7273    | 0.7619 | 0.7442 |
+| 0.0105        | 5.0   | 250  | 0.2082          | 0.945    | 0.75      | 0.7143 | 0.7317 |
+| 0.0028        | 6.0   | 300  | 0.2249          | 0.945    | 0.75      | 0.7143 | 0.7317 |
+| 0.0017        | 7.0   | 350  | 0.2379          | 0.945    | 0.7273    | 0.7619 | 0.7442 |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu118
+- Tokenizers 0.15.0

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