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--- |
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license: afl-3.0 |
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base_model: dlicari/Italian-Legal-BERT-SC |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: model |
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results: [] |
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language: |
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- it |
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library_name: transformers |
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pipeline_tag: 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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# model |
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This model is a fine-tuned version of [dlicari/Italian-Legal-BERT-SC](https://huggingface.co/dlicari/Italian-Legal-BERT-SC) on a custom dataset about financial norms. |
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## Intended uses & limitations |
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This mode has just been further pre-trained, if you intend to use it for downstream task you should fine-tune it with your data. |
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## Usage |
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To use this model you can use the following script: |
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```python |
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from transformers import AutoTokenizer, AutoModel,CamembertModel,pipeline |
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import torch |
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model = CamembertModel.from_pretrained("PeppePasti/IT-FINANCIAL-BERT") |
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tokenizer = AutoTokenizer.from_pretrained("dlicari/Italian-Legal-BERT-SC") |
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tokenizer.model_max_length=512 |
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classifier = pipeline("fill-mask", model=model, tokenizer=tokenizer) |
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classifier(" La Repubblica riconosce a tutti i <mask> il diritto al lavoro e promuove le condizioni che rendano effettivo questo diritto.") |
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``` |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 3e-06 |
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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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- gradient_accumulation_steps: 256 |
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- total_train_batch_size: 2048 |
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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: 0.5 |
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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 | Input Tokens Seen | |
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|:-------------:|:------:|:----:|:-----------------:| |
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| 0.4096 | 0.9982 | 202 | 211812352 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.3.0+cu118 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
