End of training

README.md

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+---
+license: mit
+base_model: xlm-roberta-base
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: pii_model
+  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. -->
+
+# pii_model
+
+This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0009
+- Precision: 0.7387
+- Recall: 0.7736
+- F1: 0.7558
+- 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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 192  | 0.0023          | 0.0       | 0.0    | 0.0    | 0.9993   |
+| No log        | 2.0   | 384  | 0.0012          | 0.75      | 0.7358 | 0.7429 | 0.9998   |
+| 0.036         | 3.0   | 576  | 0.0009          | 0.7009    | 0.7736 | 0.7354 | 0.9998   |
+| 0.036         | 4.0   | 768  | 0.0008          | 0.7345    | 0.7830 | 0.7580 | 0.9998   |
+| 0.036         | 5.0   | 960  | 0.0009          | 0.7387    | 0.7736 | 0.7558 | 0.9998   |
+
+
+### Framework versions
+
+- Transformers 4.38.1
+- Pytorch 2.1.2
+- Datasets 2.1.0
+- Tokenizers 0.15.2

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