---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-cased_conll2003-CRF-first-ner
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-base-cased_conll2003-CRF-first-ner

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the conll2003 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0546
- Precision: 0.6483
- Recall: 0.3940
- F1: 0.4902
- Accuracy: 0.9225

## 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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.089         | 1.0   | 7021  | 0.0522          | 0.6315    | 0.3781 | 0.4730 | 0.9193   |
| 0.0203        | 2.0   | 14042 | 0.0481          | 0.6587    | 0.4044 | 0.5011 | 0.9233   |
| 0.0166        | 3.0   | 21063 | 0.0546          | 0.6483    | 0.3940 | 0.4902 | 0.9225   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.2+cu102
- Datasets 2.2.2
- Tokenizers 0.12.1