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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- null |
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model-index: |
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- name: BibliBERT |
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results: |
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- task: |
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name: Masked Language Modeling |
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type: fill-mask |
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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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# BibliBERT |
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This model is a fine-tuned version of [dbmdz/bert-base-italian-xxl-cased](https://huggingface.co/dbmdz/bert-base-italian-xxl-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7784 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 0 |
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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: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:------:|:---------------:| |
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| 1.5764 | 1.0 | 16528 | 1.5214 | |
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| 1.4572 | 2.0 | 33056 | 1.4201 | |
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| 1.3787 | 3.0 | 49584 | 1.3728 | |
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| 1.3451 | 4.0 | 66112 | 1.3245 | |
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| 1.3066 | 5.0 | 82640 | 1.2614 | |
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| 1.2447 | 6.0 | 99168 | 1.2333 | |
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| 1.2172 | 7.0 | 115696 | 1.2149 | |
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| 1.2079 | 8.0 | 132224 | 1.1853 | |
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| 1.2167 | 9.0 | 148752 | 1.1586 | |
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| 1.2056 | 10.0 | 165280 | 1.1503 | |
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| 1.1307 | 11.0 | 181808 | 1.1224 | |
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| 1.1689 | 12.0 | 198336 | 1.1074 | |
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| 1.1007 | 13.0 | 214864 | 1.0924 | |
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| 1.0901 | 14.0 | 231392 | 1.0659 | |
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| 1.0667 | 15.0 | 247920 | 1.0650 | |
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| 1.0434 | 16.0 | 264448 | 1.0362 | |
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| 1.0333 | 17.0 | 280976 | 1.0250 | |
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| 1.0342 | 18.0 | 297504 | 1.0198 | |
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| 1.0059 | 19.0 | 314032 | 0.9950 | |
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| 0.9719 | 20.0 | 330560 | 0.9836 | |
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| 0.9863 | 21.0 | 347088 | 0.9873 | |
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| 0.9781 | 22.0 | 363616 | 0.9724 | |
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| 0.9369 | 23.0 | 380144 | 0.9599 | |
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| 0.9578 | 24.0 | 396672 | 0.9557 | |
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| 0.9253 | 25.0 | 413200 | 0.9400 | |
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| 0.9441 | 26.0 | 429728 | 0.9222 | |
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| 0.9138 | 27.0 | 446256 | 0.9140 | |
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| 0.882 | 28.0 | 462784 | 0.9045 | |
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| 0.864 | 29.0 | 479312 | 0.8880 | |
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| 0.8632 | 30.0 | 495840 | 0.9023 | |
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| 0.8342 | 32.0 | 528896 | 0.8740 | |
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| 0.8037 | 34.0 | 561952 | 0.8647 | |
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| 0.8119 | 37.0 | 611536 | 0.8358 | |
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| 0.8011 | 38.0 | 628064 | 0.8252 | |
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| 0.786 | 39.0 | 644592 | 0.8228 | |
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| 0.7697 | 41.0 | 677648 | 0.8138 | |
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| 0.7485 | 42.0 | 694176 | 0.8104 | |
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| 0.7689 | 43.0 | 710704 | 0.8018 | |
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| 0.7401 | 45.0 | 743760 | 0.7957 | |
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| 0.7031 | 47.0 | 776816 | 0.7726 | |
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| 0.7578 | 48.0 | 793344 | 0.7864 | |
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| 0.7298 | 49.0 | 809872 | 0.7775 | |
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| 0.707 | 50.0 | 826400 | 0.7784 | |
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### Framework versions |
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- Transformers 4.10.3 |
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- Pytorch 1.9.0+cu102 |
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- Datasets 1.12.1 |
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- Tokenizers 0.10.3 |
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