---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mdeberta-v3-base-subjectivity-sentiment-italian
  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. -->

# mdeberta-v3-base-subjectivity-sentiment-italian

This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6602
- Macro F1: 0.7437
- Macro P: 0.7322
- Macro R: 0.7690
- Subj F1: 0.6437
- Subj P: 0.5696
- Subj R: 0.7401
- Accuracy: 0.7826

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Macro F1 | Macro P | Macro R | Subj F1 | Subj P | Subj R | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------:|:-------:|:-------:|:------:|:------:|:--------:|
| No log        | 1.0   | 101  | 0.6392          | 0.7244   | 0.7284  | 0.7208  | 0.5913  | 0.6071 | 0.5763 | 0.7886   |
| No log        | 2.0   | 202  | 0.5375          | 0.6731   | 0.7018  | 0.7579  | 0.6064  | 0.4548 | 0.9096 | 0.6867   |
| No log        | 3.0   | 303  | 0.5731          | 0.7453   | 0.7373  | 0.7563  | 0.6349  | 0.5970 | 0.6780 | 0.7931   |
| No log        | 4.0   | 404  | 0.5788          | 0.7522   | 0.7405  | 0.7752  | 0.6534  | 0.5848 | 0.7401 | 0.7916   |
| 0.4395        | 5.0   | 505  | 0.6922          | 0.7491   | 0.7400  | 0.7628  | 0.6423  | 0.5971 | 0.6949 | 0.7946   |
| 0.4395        | 6.0   | 606  | 0.6602          | 0.7437   | 0.7322  | 0.7690  | 0.6437  | 0.5696 | 0.7401 | 0.7826   |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0