---
base_model: Musixmatch/umberto-commoncrawl-cased-v1
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: irony_classification_ita_base
  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. -->

# irony_classification_ita_base

This model is a fine-tuned version of [Musixmatch/umberto-commoncrawl-cased-v1](https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9229
- F1: 0.7035
- Roc Auc: 0.7635
- Accuracy: 0.6124

## 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: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| No log        | 1.0   | 485  | 0.4856          | 0.6741 | 0.7414  | 0.5845   |
| 0.5349        | 2.0   | 970  | 0.5023          | 0.6423 | 0.7255  | 0.6175   |
| 0.4217        | 3.0   | 1455 | 0.5592          | 0.6433 | 0.7265  | 0.6113   |
| 0.3188        | 4.0   | 1940 | 0.6664          | 0.6549 | 0.7322  | 0.6134   |
| 0.2303        | 5.0   | 2425 | 0.8518          | 0.6122 | 0.7071  | 0.6062   |
| 0.1588        | 6.0   | 2910 | 0.9229          | 0.7035 | 0.7635  | 0.6124   |
| 0.1123        | 7.0   | 3395 | 0.9859          | 0.6677 | 0.7406  | 0.6082   |
| 0.0761        | 8.0   | 3880 | 1.0392          | 0.6875 | 0.7536  | 0.6206   |
| 0.0524        | 9.0   | 4365 | 1.0789          | 0.6846 | 0.7515  | 0.6206   |
| 0.0461        | 10.0  | 4850 | 1.0948          | 0.6947 | 0.7583  | 0.6206   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.3.0+cu118
- Datasets 2.19.0
- Tokenizers 0.19.1