---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-finetuned-ner
  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-finetuned-ner

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1196
- Precision: 0.7872
- Recall: 0.8292
- F1: 0.8077
- Accuracy: 0.9722

## 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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.1243        | 1.0   | 1380 | 0.0932          | 0.6752    | 0.8222 | 0.7415 | 0.9635   |
| 0.0624        | 2.0   | 2760 | 0.0890          | 0.7298    | 0.8368 | 0.7797 | 0.9686   |
| 0.0405        | 3.0   | 4140 | 0.1029          | 0.7792    | 0.8356 | 0.8064 | 0.9715   |
| 0.0226        | 4.0   | 5520 | 0.1196          | 0.7872    | 0.8292 | 0.8077 | 0.9722   |


### Framework versions

- Transformers 4.12.5
- Pytorch 1.10.0+cu111
- Datasets 1.15.1
- Tokenizers 0.10.3