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---
library_name: transformers
license: mit
base_model: dbmdz/bert-base-italian-xxl-cased
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: bert-base-italian-xxl-cased-sentence-splitter
results: []
---
<!-- 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. -->
# bert-base-italian-xxl-cased-sentence-splitter
This model is a fine-tuned version of [dbmdz/bert-base-italian-xxl-cased](https://huggingface.co/dbmdz/bert-base-italian-xxl-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0021
- F1: 0.9938
## 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: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log | 1.0 | 49 | 0.0036 | 0.9831 |
| No log | 2.0 | 98 | 0.0021 | 0.9907 |
| No log | 3.0 | 147 | 0.0030 | 0.9861 |
| No log | 4.0 | 196 | 0.0026 | 0.9907 |
| No log | 5.0 | 245 | 0.0018 | 0.9938 |
| No log | 6.0 | 294 | 0.0020 | 0.9938 |
| No log | 7.0 | 343 | 0.0040 | 0.9861 |
| No log | 8.0 | 392 | 0.0023 | 0.9922 |
| No log | 9.0 | 441 | 0.0024 | 0.9922 |
| No log | 10.0 | 490 | 0.0062 | 0.9922 |
| 0.0139 | 11.0 | 539 | 0.0045 | 0.9891 |
| 0.0139 | 12.0 | 588 | 0.0019 | 0.9922 |
| 0.0139 | 13.0 | 637 | 0.0021 | 0.9938 |
| 0.0139 | 14.0 | 686 | 0.0024 | 0.9938 |
| 0.0139 | 15.0 | 735 | 0.0120 | 0.9891 |
| 0.0139 | 16.0 | 784 | 0.0074 | 0.9907 |
| 0.0139 | 17.0 | 833 | 0.0019 | 0.9938 |
| 0.0139 | 18.0 | 882 | 0.0019 | 0.9938 |
| 0.0139 | 19.0 | 931 | 0.0024 | 0.9922 |
| 0.0139 | 20.0 | 980 | 0.0021 | 0.9922 |
| 0.0002 | 21.0 | 1029 | 0.0021 | 0.9922 |
| 0.0002 | 22.0 | 1078 | 0.0021 | 0.9938 |
| 0.0002 | 23.0 | 1127 | 0.0022 | 0.9922 |
| 0.0002 | 24.0 | 1176 | 0.0020 | 0.9938 |
| 0.0002 | 25.0 | 1225 | 0.0022 | 0.9938 |
| 0.0002 | 26.0 | 1274 | 0.0021 | 0.9938 |
| 0.0002 | 27.0 | 1323 | 0.0022 | 0.9938 |
| 0.0002 | 28.0 | 1372 | 0.0021 | 0.9938 |
| 0.0002 | 29.0 | 1421 | 0.0021 | 0.9938 |
| 0.0002 | 30.0 | 1470 | 0.0021 | 0.9938 |
### Framework versions
- Transformers 4.55.2
- Pytorch 2.8.0+cu128
- Datasets 3.6.0
- Tokenizers 0.21.4
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