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README.md
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---
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license: apache-2.0
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base_model: studio-ousia/luke-base
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tags:
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- generated_from_trainer
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model-index:
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- name: legal-luke-base-ner
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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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# legal-luke-base-ner
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This model is a fine-tuned version of [studio-ousia/luke-base](https://huggingface.co/studio-ousia/luke-base) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0153
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- F1-type-match: 0.9297
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- F1-partial: 0.9197
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- F1-strict: 0.8794
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- F1-exact: 0.8891
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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: 0.0001
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- train_batch_size: 8
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- eval_batch_size: 8
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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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- lr_scheduler_warmup_ratio: 0.06
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | F1-type-match | F1-partial | F1-strict | F1-exact |
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|:-------------:|:-----:|:----:|:---------------:|:-------------:|:----------:|:---------:|:--------:|
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| 0.021 | 1.0 | 1375 | 0.0219 | 0.8297 | 0.8176 | 0.7238 | 0.7525 |
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| 0.0132 | 2.0 | 2750 | 0.0156 | 0.8841 | 0.8722 | 0.7943 | 0.8166 |
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| 0.0087 | 3.0 | 4125 | 0.0155 | 0.8901 | 0.8796 | 0.8271 | 0.8374 |
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| 0.0052 | 4.0 | 5500 | 0.0153 | 0.9190 | 0.9100 | 0.8633 | 0.8750 |
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| 0.0035 | 5.0 | 6875 | 0.0153 | 0.9297 | 0.9197 | 0.8794 | 0.8891 |
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### Framework versions
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- Transformers 4.36.0
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- Pytorch 2.0.0
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- Datasets 2.17.1
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- Tokenizers 0.15.0
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