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--- |
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library_name: transformers |
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license: mit |
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base_model: dbmdz/bert-base-italian-xxl-cased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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model-index: |
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- name: bert-base-italian-xxl-cased-sentence-splitter |
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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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# bert-base-italian-xxl-cased-sentence-splitter |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0026 |
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- F1: 0.9907 |
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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: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| No log | 1.0 | 49 | 0.0033 | 0.9846 | |
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| No log | 2.0 | 98 | 0.0025 | 0.9846 | |
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| No log | 3.0 | 147 | 0.0030 | 0.9861 | |
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| No log | 4.0 | 196 | 0.0033 | 0.9801 | |
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| No log | 5.0 | 245 | 0.0025 | 0.9892 | |
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| No log | 6.0 | 294 | 0.0029 | 0.9877 | |
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| No log | 7.0 | 343 | 0.0030 | 0.9907 | |
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| No log | 8.0 | 392 | 0.0023 | 0.9892 | |
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| No log | 9.0 | 441 | 0.0023 | 0.9907 | |
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| No log | 10.0 | 490 | 0.0031 | 0.9907 | |
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| 0.0128 | 11.0 | 539 | 0.0021 | 0.9922 | |
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| 0.0128 | 12.0 | 588 | 0.0038 | 0.9907 | |
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| 0.0128 | 13.0 | 637 | 0.0046 | 0.9891 | |
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| 0.0128 | 14.0 | 686 | 0.0030 | 0.9892 | |
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| 0.0128 | 15.0 | 735 | 0.0024 | 0.9907 | |
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| 0.0128 | 16.0 | 784 | 0.0023 | 0.9907 | |
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| 0.0128 | 17.0 | 833 | 0.0024 | 0.9907 | |
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| 0.0128 | 18.0 | 882 | 0.0023 | 0.9907 | |
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| 0.0128 | 19.0 | 931 | 0.0023 | 0.9907 | |
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| 0.0128 | 20.0 | 980 | 0.0024 | 0.9907 | |
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| 0.0002 | 21.0 | 1029 | 0.0024 | 0.9907 | |
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| 0.0002 | 22.0 | 1078 | 0.0024 | 0.9907 | |
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| 0.0002 | 23.0 | 1127 | 0.0024 | 0.9907 | |
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| 0.0002 | 24.0 | 1176 | 0.0025 | 0.9907 | |
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| 0.0002 | 25.0 | 1225 | 0.0025 | 0.9907 | |
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| 0.0002 | 26.0 | 1274 | 0.0025 | 0.9907 | |
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| 0.0002 | 27.0 | 1323 | 0.0025 | 0.9907 | |
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| 0.0002 | 28.0 | 1372 | 0.0026 | 0.9907 | |
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| 0.0002 | 29.0 | 1421 | 0.0026 | 0.9907 | |
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| 0.0002 | 30.0 | 1470 | 0.0026 | 0.9907 | |
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### Framework versions |
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- Transformers 4.55.0 |
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- Pytorch 2.8.0+cu128 |
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- Datasets 4.0.0 |
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- Tokenizers 0.21.4 |
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