
<!-- 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. -->

# bert-finetuned-ner

This model is a fine-tuned version of [klue/bert-base](https://huggingface.co/klue/bert-base) on the conll2003 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0943
- Precision: 0.8597
- Recall: 0.8941
- F1: 0.8766
- Accuracy: 0.9761

## 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: 8
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1321        | 1.0   | 1756 | 0.1003          | 0.8010    | 0.8514 | 0.8254 | 0.9687   |
| 0.0654        | 2.0   | 3512 | 0.0927          | 0.8331    | 0.8862 | 0.8588 | 0.9739   |
| 0.0382        | 3.0   | 5268 | 0.0943          | 0.8597    | 0.8941 | 0.8766 | 0.9761   |


### Framework versions

- Transformers 4.27.3
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "cc-by-sa-4.0", "tags": ["generated_from_trainer"], "datasets": ["conll2003"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "bert-finetuned-ner", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "conll2003", "type": "conll2003", "config": "conll2003", "split": "validation", "args": "conll2003"}, "metrics": [{"type": "precision", "value": 0.8597087378640776, "name": "Precision"}, {"type": "recall", "value": 0.8941433860652979, "name": "Recall"}, {"type": "f1", "value": 0.8765880217785844, "name": "F1"}, {"type": "accuracy", "value": 0.9760991339759331, "name": "Accuracy"}]}]}]}
transformers pytorch bert token-classification generated_from_trainer dataset:conll2003 license:cc-by-sa-4.0 model-index autotrain_compatible endpoints_compatible region:us