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