---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: apriadiazriel/bert-base-bc2gm-ner
  results: []
datasets:
- spyysalo/bc2gm_corpus
language:
- en
library_name: transformers
---

<!-- This model card has been generated automatically according to the information Keras had access to. You should
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# apriadiazriel/bert-base-bc2gm-ner

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the [BC2GM Corpus](https://huggingface.co/datasets/spyysalo/bc2gm_corpus).
It achieves the following results on the evaluation set:
- Train Loss: 0.0035
- Validation Loss: 0.1569
- Precision: 0.8494
- Recall: 0.8766
- F1: 0.8628
- Accuracy: 0.9714
- Epoch: 9

## 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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 15620, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Precision | Recall | F1 | Accuracy | Epoch |
|:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
| 0.1451     | 0.0924          | 0.8182          | 0.8184       | 0.8183   | 0.9647         | 0     |
| 0.0718     | 0.0859          | 0.8272          | 0.8595       | 0.8431   | 0.9687         | 1     |
| 0.0444     | 0.1031          | 0.8597          | 0.8478       | 0.8537   | 0.9697         | 2     |
| 0.0270     | 0.1078          | 0.8459          | 0.8633       | 0.8545   | 0.9697         | 3     |
| 0.0179     | 0.1165          | 0.8556          | 0.8646       | 0.8601   | 0.9708         | 4     |
| 0.0133     | 0.1281          | 0.8514          | 0.8701       | 0.8606   | 0.9712         | 5     |
| 0.0083     | 0.1469          | 0.8293          | 0.8889       | 0.8581   | 0.9691         | 6     |
| 0.0059     | 0.1568          | 0.8450          | 0.8808       | 0.8625   | 0.9709         | 7     |
| 0.0045     | 0.1540          | 0.8519          | 0.8760       | 0.8638   | 0.9714         | 8     |
| 0.0035     | 0.1569          | 0.8494          | 0.8766       | 0.8628   | 0.9714         | 9     |


### Framework versions

- Transformers 4.31.0
- TensorFlow 2.10.1
- Datasets 3.0.0
- Tokenizers 0.13.3