---
library_name: transformers
base_model: Musixmatch/umberto-commoncrawl-cased-v1
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: multipride_umberto
  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. -->

# multipride_umberto

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: 0.3664
- Accuracy: 0.9202
- Precision: 0.9015
- Recall: 0.8273
- F1: 0.8578

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.3334        | 1.0   | 95   | 0.3002          | 0.9080   | 0.9239    | 0.7704 | 0.8199 |
| 0.2216        | 2.0   | 190  | 0.2308          | 0.9141   | 0.9285    | 0.7865 | 0.8346 |
| 0.1196        | 3.0   | 285  | 0.3063          | 0.9202   | 0.8593    | 0.9014 | 0.8779 |
| 0.0925        | 4.0   | 380  | 0.3114          | 0.9264   | 0.8965    | 0.8558 | 0.8742 |
| 0.0292        | 5.0   | 475  | 0.3664          | 0.9202   | 0.9015    | 0.8273 | 0.8578 |


### Framework versions

- Transformers 4.57.2
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1