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update model card README.md
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README.md
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---
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license: cc-by-sa-4.0
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tags:
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- generated_from_trainer
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datasets:
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- lex_glue
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model-index:
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- name: ECHR_test_Merged
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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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# ECHR_test_Merged
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This model is a fine-tuned version of [nlpaueb/legal-bert-base-uncased](https://huggingface.co/nlpaueb/legal-bert-base-uncased) on the lex_glue dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2162
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- Macro-f1: 0.5607
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- Micro-f1: 0.6726
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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: 3e-05
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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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- num_epochs: 10
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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 | Macro-f1 | Micro-f1 |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|
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| 0.2278 | 0.44 | 500 | 0.3196 | 0.2394 | 0.4569 |
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| 0.1891 | 0.89 | 1000 | 0.2827 | 0.3255 | 0.5112 |
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| 0.1803 | 1.33 | 1500 | 0.2603 | 0.3961 | 0.5698 |
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| 0.1676 | 1.78 | 2000 | 0.2590 | 0.4251 | 0.6003 |
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| 0.1635 | 2.22 | 2500 | 0.2489 | 0.4186 | 0.6030 |
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| 0.1784 | 2.67 | 3000 | 0.2445 | 0.4627 | 0.6159 |
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| 0.1556 | 3.11 | 3500 | 0.2398 | 0.4757 | 0.6170 |
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| 0.151 | 3.56 | 4000 | 0.2489 | 0.4725 | 0.6163 |
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| 0.1564 | 4.0 | 4500 | 0.2289 | 0.5019 | 0.6416 |
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| 0.1544 | 4.44 | 5000 | 0.2406 | 0.5013 | 0.6408 |
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| 0.1516 | 4.89 | 5500 | 0.2351 | 0.5145 | 0.6510 |
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| 0.1487 | 5.33 | 6000 | 0.2354 | 0.5164 | 0.6394 |
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| 0.1385 | 5.78 | 6500 | 0.2385 | 0.5205 | 0.6486 |
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| 0.145 | 6.22 | 7000 | 0.2337 | 0.5197 | 0.6529 |
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| 0.1332 | 6.67 | 7500 | 0.2294 | 0.5421 | 0.6526 |
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| 0.1293 | 7.11 | 8000 | 0.2167 | 0.5576 | 0.6652 |
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| 0.1475 | 7.56 | 8500 | 0.2218 | 0.5676 | 0.6649 |
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| 0.1376 | 8.0 | 9000 | 0.2203 | 0.5565 | 0.6709 |
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| 0.1408 | 8.44 | 9500 | 0.2178 | 0.5541 | 0.6716 |
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| 0.133 | 8.89 | 10000 | 0.2212 | 0.5692 | 0.6640 |
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| 0.1363 | 9.33 | 10500 | 0.2148 | 0.5642 | 0.6736 |
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| 0.1344 | 9.78 | 11000 | 0.2162 | 0.5607 | 0.6726 |
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### Framework versions
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- Transformers 4.19.4
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- Pytorch 1.11.0+cu113
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- Datasets 2.2.2
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- Tokenizers 0.12.1
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