End of training

README.md

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+---
+license: mit
+base_model: neuralmind/bert-base-portuguese-cased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: nees-bert-base-portuguese-cased-finetuned-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. -->
+
+# nees-bert-base-portuguese-cased-finetuned-ner
+
+This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0255
+- Precision: 0.6545
+- Recall: 0.7802
+- F1: 0.7119
+- Accuracy: 0.9952
+
+## 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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0344        | 1.0   | 519  | 0.0189          | 0.0       | 0.0    | 0.0    | 0.9949   |
+| 0.0145        | 2.0   | 1038 | 0.0112          | 0.5050    | 0.4737 | 0.4888 | 0.9952   |
+| 0.0121        | 3.0   | 1557 | 0.0132          | 0.3684    | 0.1300 | 0.1922 | 0.9953   |
+| 0.0107        | 4.0   | 2076 | 0.0239          | 0.6366    | 0.7647 | 0.6948 | 0.9955   |
+| 0.0056        | 5.0   | 2595 | 0.0151          | 0.6845    | 0.7121 | 0.6980 | 0.9950   |
+| 0.0053        | 6.0   | 3114 | 0.0278          | 0.6432    | 0.7368 | 0.6869 | 0.9943   |
+| 0.0047        | 7.0   | 3633 | 0.0199          | 0.5682    | 0.7740 | 0.6553 | 0.9953   |
+| 0.0043        | 8.0   | 4152 | 0.0231          | 0.6429    | 0.7802 | 0.7049 | 0.9951   |
+| 0.0022        | 9.0   | 4671 | 0.0255          | 0.6487    | 0.7833 | 0.7097 | 0.9955   |
+| 0.0025        | 10.0  | 5190 | 0.0255          | 0.6545    | 0.7802 | 0.7119 | 0.9952   |
+
+
+### Framework versions
+
+- Transformers 4.37.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.17.1
+- Tokenizers 0.15.2

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