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

# target_classification_ita

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: 0.6432
- F1: 0.7407
- Roc Auc: 0.7843
- Accuracy: 0.6735

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|
| 0.5508        | 1.0   | 1037  | 0.5281          | 0.6704 | 0.7301  | 0.6151   |
| 0.4816        | 2.0   | 2074  | 0.4964          | 0.7109 | 0.7631  | 0.6770   |
| 0.4004        | 3.0   | 3111  | 0.5246          | 0.7299 | 0.7743  | 0.6701   |
| 0.3353        | 4.0   | 4148  | 0.5791          | 0.7310 | 0.7767  | 0.6718   |
| 0.2731        | 5.0   | 5185  | 0.6432          | 0.7407 | 0.7843  | 0.6735   |
| 0.2271        | 6.0   | 6222  | 0.6896          | 0.7248 | 0.7710  | 0.6460   |
| 0.1842        | 7.0   | 7259  | 0.7441          | 0.7271 | 0.7757  | 0.6667   |
| 0.15          | 8.0   | 8296  | 0.8640          | 0.7301 | 0.7769  | 0.6632   |
| 0.1123        | 9.0   | 9333  | 0.9447          | 0.7356 | 0.7812  | 0.6701   |
| 0.0973        | 10.0  | 10370 | 0.9652          | 0.7310 | 0.7773  | 0.6632   |


### Framework versions

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