---
library_name: transformers
license: apache-2.0
base_model: nickprock/setfit-italian-hate-speech
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: MultiPRIDE-DualEncoder-LPFT-it
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# MultiPRIDE-DualEncoder-LPFT-it

This model is a fine-tuned version of [nickprock/setfit-italian-hate-speech](https://huggingface.co/nickprock/setfit-italian-hate-speech) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0299
- Accuracy: 0.9080
- F1: 0.7619
- Precision: 0.75
- Recall: 0.7742

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 150
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.2105        | 1.0   | 95   | 0.1445          | 0.7914   | 0.32   | 0.4211    | 0.2581 |
| 0.1483        | 2.0   | 190  | 0.0919          | 0.8650   | 0.6452 | 0.6452    | 0.6452 |
| 0.095         | 3.0   | 285  | 0.0521          | 0.9202   | 0.7869 | 0.8       | 0.7742 |
| 0.0505        | 4.0   | 380  | 0.0327          | 0.9018   | 0.7576 | 0.7143    | 0.8065 |
| 0.0361        | 5.0   | 475  | 0.0309          | 0.8957   | 0.7302 | 0.7188    | 0.7419 |
| 0.0305        | 6.0   | 570  | 0.0299          | 0.9080   | 0.7619 | 0.75      | 0.7742 |


### Framework versions

- Transformers 4.57.3
- Pytorch 2.9.1+cu128
- Datasets 4.4.1
- Tokenizers 0.22.1