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README.md
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---
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language:
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- en
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license: mit
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base_model: prajjwal1/bert-tiny
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tags:
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- pytorch
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- BertForTokenClassification
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- bert-tiny
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- nammed-entity-recogntion
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- generated_from_trainer
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model-index:
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- name: bert-tiny-privacy
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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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# bert-tiny-privacy
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This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on the beki/privy dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0235
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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: 4e-05
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- train_batch_size: 32
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- eval_batch_size: 128
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- seed: 13434865
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.01
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- training_steps: 15000
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:-----:|:---------------:|
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| 0.1891 | 0.19 | 2500 | 0.1369 |
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| 0.0869 | 0.38 | 5000 | 0.0503 |
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| 0.0609 | 0.57 | 7500 | 0.0314 |
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| 0.0512 | 0.76 | 10000 | 0.0259 |
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| 0.0493 | 0.95 | 12500 | 0.0240 |
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| 0.048 | 1.14 | 15000 | 0.0237 |
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### Framework versions
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- Transformers 4.36.2
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- Pytorch 2.1.0+cu121
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- Datasets 2.16.0
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- Tokenizers 0.15.0
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