---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-NER-finetuned-ner-cerec
  results: []
---

<!-- 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-base-NER-finetuned-ner-cerec

This model is a fine-tuned version of [dslim/bert-base-NER](https://huggingface.co/dslim/bert-base-NER) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2862
- Precision: 0.8235
- Recall: 0.6853
- F1: 0.7481
- Accuracy: 0.9517

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 45   | 0.5671          | 0.6       | 0.5455 | 0.5714 | 0.9167   |
| No log        | 2.0   | 90   | 0.3043          | 0.7667    | 0.6434 | 0.6996 | 0.9447   |
| No log        | 3.0   | 135  | 0.2862          | 0.8235    | 0.6853 | 0.7481 | 0.9517   |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.12.1
- Datasets 2.10.1
- Tokenizers 0.11.0