---
license: mit
base_model: neuraly/bert-base-italian-cased-sentiment
tags:
- generated_from_trainer
datasets:
- tweet_sentiment_multilingual
metrics:
- accuracy
model-index:
- name: sentiment_ita
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: tweet_sentiment_multilingual
      type: tweet_sentiment_multilingual
      config: italian
      split: validation
      args: italian
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6851851851851852
---

<!-- 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. -->

# sentiment_ita

This model is a fine-tuned version of [neuraly/bert-base-italian-cased-sentiment](https://huggingface.co/neuraly/bert-base-italian-cased-sentiment) on the tweet_sentiment_multilingual dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5199
- Accuracy: 0.6852

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 170  | 1.1582          | 0.6173   |
| No log        | 2.0   | 340  | 0.8326          | 0.6389   |
| 1.0735        | 3.0   | 510  | 0.7827          | 0.6543   |
| 1.0735        | 4.0   | 680  | 0.7898          | 0.6728   |
| 1.0735        | 5.0   | 850  | 0.8674          | 0.6759   |
| 0.4509        | 6.0   | 1020 | 1.0103          | 0.6883   |
| 0.4509        | 7.0   | 1190 | 1.1162          | 0.7006   |
| 0.4509        | 8.0   | 1360 | 1.3433          | 0.6883   |
| 0.1439        | 9.0   | 1530 | 1.4674          | 0.6821   |
| 0.1439        | 10.0  | 1700 | 1.5199          | 0.6852   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.0.1
- Datasets 2.15.0
- Tokenizers 0.15.0