---
library_name: transformers
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-multilingual-uncased-finetuned-ner-prostata
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-base-multilingual-uncased-finetuned-ner-prostata

This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0424
- Precision: 0.9601
- Recall: 0.9635
- F1: 0.9618
- Accuracy: 0.9935

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 389  | 0.0228          | 0.9692    | 0.9773 | 0.9733 | 0.9952   |
| 0.0266        | 2.0   | 778  | 0.0285          | 0.9733    | 0.9657 | 0.9695 | 0.9939   |
| 0.0153        | 3.0   | 1167 | 0.0257          | 0.9817    | 0.9741 | 0.9779 | 0.9955   |
| 0.014         | 4.0   | 1556 | 0.0285          | 0.9817    | 0.9728 | 0.9772 | 0.9950   |
| 0.014         | 5.0   | 1945 | 0.0261          | 0.9761    | 0.9799 | 0.9780 | 0.9954   |
| 0.0129        | 6.0   | 2334 | 0.0254          | 0.9818    | 0.9767 | 0.9792 | 0.9957   |
| 0.0113        | 7.0   | 2723 | 0.0255          | 0.9844    | 0.9793 | 0.9818 | 0.9962   |
| 0.0078        | 8.0   | 3112 | 0.0246          | 0.9812    | 0.9793 | 0.9802 | 0.9960   |
| 0.0065        | 9.0   | 3501 | 0.0261          | 0.9850    | 0.9799 | 0.9825 | 0.9961   |
| 0.0065        | 10.0  | 3890 | 0.0257          | 0.9838    | 0.9806 | 0.9822 | 0.9961   |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1