---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: multipride_umberto_ner
  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_ner

This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2343
- Accuracy: 0.9325
- Precision: 0.9026
- Recall: 0.8719
- F1: 0.8862

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.491         | 1.0   | 95   | 0.3350          | 0.9018   | 0.9459    | 0.7419 | 0.7975 |
| 0.2737        | 2.0   | 190  | 0.3016          | 0.9080   | 0.8771    | 0.8074 | 0.8360 |
| 0.2221        | 3.0   | 285  | 0.3218          | 0.8896   | 0.8137    | 0.9071 | 0.8456 |
| 0.2015        | 4.0   | 380  | 0.2428          | 0.9264   | 0.8805    | 0.8805 | 0.8805 |
| 0.1783        | 5.0   | 475  | 0.2343          | 0.9325   | 0.9026    | 0.8719 | 0.8862 |


### Framework versions

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