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

# bert-base-uncased-finetuned-ner-prostata

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1427
- Precision: 0.9238
- Recall: 0.9494
- F1: 0.9364
- Accuracy: 0.9755

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1389        | 1.0   | 2395  | 0.1002          | 0.9331    | 0.9256 | 0.9293 | 0.9750   |
| 0.09          | 2.0   | 4790  | 0.0930          | 0.9334    | 0.9573 | 0.9452 | 0.9795   |
| 0.0608        | 3.0   | 7185  | 0.0983          | 0.9275    | 0.9525 | 0.9399 | 0.9770   |
| 0.0541        | 4.0   | 9580  | 0.1011          | 0.9390    | 0.9553 | 0.9471 | 0.9793   |
| 0.0447        | 5.0   | 11975 | 0.1060          | 0.9348    | 0.9489 | 0.9418 | 0.9789   |
| 0.0383        | 6.0   | 14370 | 0.1128          | 0.9324    | 0.9506 | 0.9414 | 0.9782   |
| 0.0306        | 7.0   | 16765 | 0.1130          | 0.9395    | 0.9493 | 0.9443 | 0.9795   |
| 0.0286        | 8.0   | 19160 | 0.1200          | 0.9331    | 0.9519 | 0.9424 | 0.9787   |
| 0.024         | 9.0   | 21555 | 0.1215          | 0.9352    | 0.9500 | 0.9425 | 0.9788   |
| 0.0213        | 10.0  | 23950 | 0.1242          | 0.9370    | 0.9488 | 0.9428 | 0.9788   |


### Framework versions

- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1