---
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-MainStage-it
  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. -->

# MultiPRIDE-DualEncoder-MainStage-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: 0.1685
- Accuracy: 0.9571
- F1: 0.8814
- Precision: 0.9286
- Recall: 0.8387

## 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: 1337
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6452        | 1.0   | 95   | 0.5242          | 0.8344   | 0.6197 | 0.55      | 0.7097 |
| 0.5208        | 2.0   | 190  | 0.3521          | 0.8896   | 0.7273 | 0.6857    | 0.7742 |
| 0.4215        | 3.0   | 285  | 0.2637          | 0.9325   | 0.8136 | 0.8571    | 0.7742 |
| 0.3325        | 4.0   | 380  | 0.2138          | 0.9325   | 0.8136 | 0.8571    | 0.7742 |
| 0.2774        | 5.0   | 475  | 0.1805          | 0.9448   | 0.8525 | 0.8667    | 0.8387 |
| 0.2297        | 6.0   | 570  | 0.1846          | 0.9509   | 0.8621 | 0.9259    | 0.8065 |
| 0.3021        | 7.0   | 665  | 0.1664          | 0.9509   | 0.8667 | 0.8966    | 0.8387 |
| 0.2372        | 8.0   | 760  | 0.1697          | 0.9571   | 0.8814 | 0.9286    | 0.8387 |
| 0.2468        | 9.0   | 855  | 0.1688          | 0.9571   | 0.8814 | 0.9286    | 0.8387 |
| 0.2456        | 10.0  | 950  | 0.1685          | 0.9571   | 0.8814 | 0.9286    | 0.8387 |


### Framework versions

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