--- license: apache-2.0 tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model_index: - name: portuguese-archival-finding-aids results: - task: name: Token Classification type: token-classification metric: name: Accuracy type: accuracy value: 0.9617770479839446 --- # portuguese-archival-finding-aids This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co./bert-base-multilingual-cased) on an unkown dataset. It achieves the following results on the evaluation set: - Loss: 0.1812 - Precision: 0.8624 - Recall: 0.9557 - F1: 0.9067 - Accuracy: 0.9618 ## 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: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | No log | 1.0 | 192 | 0.1565 | 0.8511 | 0.9327 | 0.8900 | 0.9563 | | 0.1849 | 2.0 | 384 | 0.1594 | 0.8634 | 0.9543 | 0.9065 | 0.9619 | | 0.0454 | 3.0 | 576 | 0.1812 | 0.8624 | 0.9557 | 0.9067 | 0.9618 | ### Framework versions - Transformers 4.10.0.dev0 - Pytorch 1.9.0+cu111 - Datasets 1.10.2 - Tokenizers 0.10.3