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README.md
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---
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license: mit
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: bert-italian-xxl-cased-ItaCoLA
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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-italian-xxl-cased-ItaCoLA
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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: 0.5610
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- Accuracy: 0.8943
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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: 1e-05
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- train_batch_size: 32
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: constant
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 10.0
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.4243 | 0.41 | 100 | 0.3805 | 0.8541 |
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| 0.3806 | 0.82 | 200 | 0.3862 | 0.8573 |
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| 0.3289 | 1.23 | 300 | 0.3537 | 0.8679 |
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| 0.2967 | 1.64 | 400 | 0.3165 | 0.8827 |
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| 0.2992 | 2.05 | 500 | 0.3382 | 0.8784 |
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| 0.2273 | 2.46 | 600 | 0.3294 | 0.8816 |
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| 0.2215 | 2.87 | 700 | 0.3049 | 0.8911 |
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| 0.1718 | 3.28 | 800 | 0.3531 | 0.8911 |
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| 0.1757 | 3.69 | 900 | 0.3903 | 0.8922 |
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| 0.1698 | 4.1 | 1000 | 0.3871 | 0.8953 |
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| 0.1307 | 4.51 | 1100 | 0.4255 | 0.8953 |
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| 0.1426 | 4.92 | 1200 | 0.3729 | 0.8985 |
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| 0.1136 | 5.33 | 1300 | 0.4939 | 0.8964 |
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| 0.1163 | 5.74 | 1400 | 0.4004 | 0.8964 |
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| 0.0936 | 6.15 | 1500 | 0.5116 | 0.8964 |
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| 0.0973 | 6.56 | 1600 | 0.4808 | 0.8922 |
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| 0.0899 | 6.97 | 1700 | 0.4813 | 0.8869 |
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| 0.0687 | 7.38 | 1800 | 0.6046 | 0.8848 |
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| 0.0709 | 7.79 | 1900 | 0.5940 | 0.8964 |
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| 0.0694 | 8.2 | 2000 | 0.5791 | 0.8911 |
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| 0.0732 | 8.61 | 2100 | 0.5577 | 0.8922 |
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| 0.0714 | 9.02 | 2200 | 0.5249 | 0.8996 |
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| 0.0531 | 9.43 | 2300 | 0.6098 | 0.8932 |
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| 0.0713 | 9.84 | 2400 | 0.5610 | 0.8943 |
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### Framework versions
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- Transformers 4.28.1
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- Pytorch 2.0.1+cu117
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- Datasets 2.12.0
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- Tokenizers 0.13.3
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