metadata
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-NER-finetuned-ner-cerec
results: []
bert-base-NER-finetuned-ner-cerec
This model is a fine-tuned version of dslim/bert-base-NER on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1511
- Precision: 0.8652
- Recall: 0.8531
- F1: 0.8592
- Accuracy: 0.9790
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 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 45 | 0.4929 | 0.6532 | 0.5664 | 0.6067 | 0.9237 |
| No log | 2.0 | 90 | 0.3090 | 0.8145 | 0.7063 | 0.7566 | 0.9497 |
| No log | 3.0 | 135 | 0.2477 | 0.8433 | 0.7902 | 0.8159 | 0.9625 |
| No log | 4.0 | 180 | 0.2209 | 0.8169 | 0.8112 | 0.8140 | 0.9669 |
| No log | 5.0 | 225 | 0.1906 | 0.8369 | 0.8252 | 0.8310 | 0.9739 |
| No log | 6.0 | 270 | 0.1568 | 0.8662 | 0.8601 | 0.8632 | 0.9784 |
| No log | 7.0 | 315 | 0.1532 | 0.8732 | 0.8671 | 0.8702 | 0.9790 |
| No log | 8.0 | 360 | 0.1530 | 0.8671 | 0.8671 | 0.8671 | 0.9790 |
| No log | 9.0 | 405 | 0.1526 | 0.8723 | 0.8601 | 0.8662 | 0.9790 |
| No log | 10.0 | 450 | 0.1511 | 0.8652 | 0.8531 | 0.8592 | 0.9790 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1
- Datasets 2.10.1
- Tokenizers 0.11.0