---
base_model: Musixmatch/umberto-commoncrawl-cased-v1
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: target_classification_ita2
  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_ita2

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: 0.3451
- F1: 0.4422
- Roc Auc: 0.6814
- Accuracy: 0.8127

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.4759        | 1.0   | 897  | 0.2585          | 0.0794 | 0.5170  | 0.8093   |
| 0.3547        | 2.0   | 1794 | 0.2457          | 0.2517 | 0.5753  | 0.8230   |
| 0.2756        | 3.0   | 2691 | 0.2561          | 0.4138 | 0.6693  | 0.8007   |
| 0.1996        | 4.0   | 3588 | 0.2704          | 0.3929 | 0.6400  | 0.8299   |
| 0.1529        | 5.0   | 4485 | 0.3451          | 0.4422 | 0.6814  | 0.8127   |
| 0.1057        | 6.0   | 5382 | 0.4442          | 0.3605 | 0.6279  | 0.8196   |
| 0.0644        | 7.0   | 6279 | 0.4965          | 0.3858 | 0.6518  | 0.7973   |
| 0.045         | 8.0   | 7176 | 0.5365          | 0.3867 | 0.6440  | 0.8179   |
| 0.0328        | 9.0   | 8073 | 0.5268          | 0.4046 | 0.6478  | 0.8316   |
| 0.0275        | 10.0  | 8970 | 0.5573          | 0.4044 | 0.6533  | 0.8213   |


### Framework versions

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