Training completed!
Browse files
README.md
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---
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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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model-index:
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- name: deberta-pii-finetuned
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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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# deberta-pii-finetuned
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This model was trained from scratch on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0033
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- F Beta: 0.7862
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- Precision: 0.9914
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- Recall: 0.7797
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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: 5e-06
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- train_batch_size: 8
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- eval_batch_size: 16
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- seed: 42
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- gradient_accumulation_steps: 3
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- total_train_batch_size: 24
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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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- num_epochs: 1
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F Beta | Precision | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|
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| 0.0001 | 0.27 | 70 | 0.0119 | 0.3263 | 0.9775 | 0.3178 |
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| 0.002 | 0.54 | 140 | 0.0044 | 0.7110 | 0.9904 | 0.7030 |
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| 0.0003 | 0.82 | 210 | 0.0033 | 0.7862 | 0.9914 | 0.7797 |
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### Framework versions
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- Transformers 4.37.2
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- Pytorch 2.0.0
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- Datasets 2.1.0
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- Tokenizers 0.15.0
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runs/Feb17_05-47-38_7f7d15bc24af/events.out.tfevents.1708148874.7f7d15bc24af.26.0
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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size 20115
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