---
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