---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: haspeech_ita
  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. -->

# haspeech_ita

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1077
- Accuracy: 0.9837

## 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: 24
- eval_batch_size: 8
- 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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6174        | 0.72  | 100  | 0.5599          | 0.7425   |
| 0.5737        | 1.44  | 200  | 0.4727          | 0.7886   |
| 0.4188        | 2.16  | 300  | 0.3844          | 0.8482   |
| 0.2411        | 2.88  | 400  | 0.1425          | 0.9566   |
| 0.1376        | 3.6   | 500  | 0.1483          | 0.9566   |
| 0.1045        | 4.32  | 600  | 0.1069          | 0.9783   |
| 0.0485        | 5.04  | 700  | 0.1390          | 0.9783   |
| 0.0217        | 5.76  | 800  | 0.0962          | 0.9864   |
| 0.0137        | 6.47  | 900  | 0.0788          | 0.9892   |
| 0.0049        | 7.19  | 1000 | 0.1223          | 0.9810   |
| 0.0043        | 7.91  | 1100 | 0.1077          | 0.9837   |


### Framework versions

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