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---
tags:
- generated_from_trainer
datasets:
- null
model-index:
- name: BibliBERT
results:
- task:
name: Masked Language Modeling
type: fill-mask
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# BibliBERT
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.
It achieves the following results on the evaluation set:
- Loss: 0.7784
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 0
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:------:|:---------------:|
| 1.5764 | 1.0 | 16528 | 1.5214 |
| 1.4572 | 2.0 | 33056 | 1.4201 |
| 1.3787 | 3.0 | 49584 | 1.3728 |
| 1.3451 | 4.0 | 66112 | 1.3245 |
| 1.3066 | 5.0 | 82640 | 1.2614 |
| 1.2447 | 6.0 | 99168 | 1.2333 |
| 1.2172 | 7.0 | 115696 | 1.2149 |
| 1.2079 | 8.0 | 132224 | 1.1853 |
| 1.2167 | 9.0 | 148752 | 1.1586 |
| 1.2056 | 10.0 | 165280 | 1.1503 |
| 1.1307 | 11.0 | 181808 | 1.1224 |
| 1.1689 | 12.0 | 198336 | 1.1074 |
| 1.1007 | 13.0 | 214864 | 1.0924 |
| 1.0901 | 14.0 | 231392 | 1.0659 |
| 1.0667 | 15.0 | 247920 | 1.0650 |
| 1.0434 | 16.0 | 264448 | 1.0362 |
| 1.0333 | 17.0 | 280976 | 1.0250 |
| 1.0342 | 18.0 | 297504 | 1.0198 |
| 1.0059 | 19.0 | 314032 | 0.9950 |
| 0.9719 | 20.0 | 330560 | 0.9836 |
| 0.9863 | 21.0 | 347088 | 0.9873 |
| 0.9781 | 22.0 | 363616 | 0.9724 |
| 0.9369 | 23.0 | 380144 | 0.9599 |
| 0.9578 | 24.0 | 396672 | 0.9557 |
| 0.9253 | 25.0 | 413200 | 0.9400 |
| 0.9441 | 26.0 | 429728 | 0.9222 |
| 0.9138 | 27.0 | 446256 | 0.9140 |
| 0.882 | 28.0 | 462784 | 0.9045 |
| 0.864 | 29.0 | 479312 | 0.8880 |
| 0.8632 | 30.0 | 495840 | 0.9023 |
| 0.8342 | 32.0 | 528896 | 0.8740 |
| 0.8037 | 34.0 | 561952 | 0.8647 |
| 0.8119 | 37.0 | 611536 | 0.8358 |
| 0.8011 | 38.0 | 628064 | 0.8252 |
| 0.786 | 39.0 | 644592 | 0.8228 |
| 0.7697 | 41.0 | 677648 | 0.8138 |
| 0.7485 | 42.0 | 694176 | 0.8104 |
| 0.7689 | 43.0 | 710704 | 0.8018 |
| 0.7401 | 45.0 | 743760 | 0.7957 |
| 0.7031 | 47.0 | 776816 | 0.7726 |
| 0.7578 | 48.0 | 793344 | 0.7864 |
| 0.7298 | 49.0 | 809872 | 0.7775 |
| 0.707 | 50.0 | 826400 | 0.7784 |
### Framework versions
- Transformers 4.10.3
- Pytorch 1.9.0+cu102
- Datasets 1.12.1
- Tokenizers 0.10.3
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