---
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: 0.0215
- Accuracy: 0.9202
- F1: 0.8060
- Precision: 0.75
- Recall: 0.8710

## 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: 67
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.1723        | 1.0   | 95   | 0.1277          | 0.8037   | 0.5556 | 0.4878    | 0.6452 |
| 0.1278        | 2.0   | 190  | 0.0812          | 0.9325   | 0.8    | 0.9167    | 0.7097 |
| 0.0705        | 3.0   | 285  | 0.0408          | 0.9571   | 0.8889 | 0.875     | 0.9032 |
| 0.0463        | 4.0   | 380  | 0.0261          | 0.9509   | 0.8788 | 0.8286    | 0.9355 |
| 0.0329        | 5.0   | 475  | 0.0216          | 0.9325   | 0.8406 | 0.7632    | 0.9355 |
| 0.0237        | 6.0   | 570  | 0.0215          | 0.9202   | 0.8060 | 0.75      | 0.8710 |


### Framework versions

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