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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
probably proofread and complete it, then remove this comment. -->
# 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 |