---
license: mit
base_model: MilaNLProc/hate-ita-xlm-r-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: haspeech_ita
  results: []
language:
- it
datasets:
- Paul/hatecheck-italian
---

<!-- 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. -->

# haspeech_ita

This model is a fine-tuned version of [MilaNLProc/hate-ita-xlm-r-large](https://huggingface.co/MilaNLProc/hate-ita-xlm-r-large) 
on a dataset [Paul/hatecheck-italian](https://huggingface.co/datasets/Paul/hatecheck-italian).
It achieves the following results on the evaluation set:
- Loss: 0.0030
- Accuracy: 0.9973

## 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: 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: 500
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3538        | 0.48  | 100  | 0.2109          | 0.9241   |
| 0.18          | 0.96  | 200  | 0.1058          | 0.9783   |
| 0.0924        | 1.44  | 300  | 0.0618          | 0.9892   |
| 0.0948        | 1.92  | 400  | 0.0382          | 0.9892   |
| 0.0475        | 2.4   | 500  | 0.0607          | 0.9919   |
| 0.0572        | 2.88  | 600  | 0.0030          | 0.9973   |


### Framework versions

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