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End of training
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README.md
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---
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license: apache-2.0
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base_model: distilbert/distilbert-base-multilingual-cased
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: piimasking_pytorch
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# piimasking_pytorch
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This model is a fine-tuned version of [distilbert/distilbert-base-multilingual-cased](https://huggingface.co/distilbert/distilbert-base-multilingual-cased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0654
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- Precision: 0.9137
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- Recall: 0.9428
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- F1: 0.9280
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- Accuracy: 0.9751
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.0854 | 1.0 | 10463 | 0.0744 | 0.9116 | 0.9312 | 0.9213 | 0.9700 |
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| 0.064 | 2.0 | 20926 | 0.0629 | 0.9109 | 0.9387 | 0.9246 | 0.9749 |
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| 0.0483 | 3.0 | 31389 | 0.0654 | 0.9137 | 0.9428 | 0.9280 | 0.9751 |
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### Framework versions
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- Transformers 4.41.0
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- Pytorch 2.3.0+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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model.safetensors
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