End of training

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: piidetection
+  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. -->
+
+# piidetection
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0010
+- Precision: 0.7422
+- Recall: 0.8051
+- F1: 0.7724
+- Accuracy: 0.9998
+
+## 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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 171  | 0.0044          | 0.0       | 0.0    | 0.0    | 0.9993   |
+| No log        | 2.0   | 342  | 0.0018          | 0.4084    | 0.3305 | 0.3653 | 0.9996   |
+| 0.0316        | 3.0   | 513  | 0.0013          | 0.7661    | 0.5551 | 0.6437 | 0.9997   |
+| 0.0316        | 4.0   | 684  | 0.0010          | 0.7258    | 0.7627 | 0.7438 | 0.9998   |
+| 0.0316        | 5.0   | 855  | 0.0010          | 0.7991    | 0.7585 | 0.7783 | 0.9998   |
+| 0.0008        | 6.0   | 1026 | 0.0009          | 0.7317    | 0.7627 | 0.7469 | 0.9998   |
+| 0.0008        | 7.0   | 1197 | 0.0010          | 0.7449    | 0.7669 | 0.7557 | 0.9998   |
+| 0.0008        | 8.0   | 1368 | 0.0011          | 0.7965    | 0.7627 | 0.7792 | 0.9998   |
+| 0.0004        | 9.0   | 1539 | 0.0010          | 0.7520    | 0.7839 | 0.7676 | 0.9998   |
+| 0.0004        | 10.0  | 1710 | 0.0010          | 0.7422    | 0.8051 | 0.7724 | 0.9998   |
+
+
+### Framework versions
+
+- Transformers 4.37.0
+- Pytorch 2.1.2
+- Datasets 2.1.0
+- Tokenizers 0.15.1

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