---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
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-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.

## 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: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy | B-location-precision | B-location-recall | B-location-f1 | I-location-precision | I-location-recall | I-location-f1 | B-group-precision | B-group-recall | B-group-f1 | I-group-precision | I-group-recall | I-group-f1 | B-corporation-precision | B-corporation-recall | B-corporation-f1 | I-corporation-precision | I-corporation-recall | I-corporation-f1 | B-person-precision | B-person-recall | B-person-f1 | I-person-precision | I-person-recall | I-person-f1 | B-creative-work-precision | B-creative-work-recall | B-creative-work-f1 | I-creative-work-precision | I-creative-work-recall | I-creative-work-f1 | B-product-precision | B-product-recall | B-product-f1 | I-product-precision | I-product-recall | I-product-f1 | Corporation-precision | Corporation-recall | Corporation-f1 | Corporation-number | Creative-work-precision | Creative-work-recall | Creative-work-f1 | Creative-work-number | Group-precision | Group-recall | Group-f1 | Group-number | Location-precision | Location-recall | Location-f1 | Location-number | Person-precision | Person-recall | Person-f1 | Person-number | Product-precision | Product-recall | Product-f1 | Product-number |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:--------------------:|:-----------------:|:-------------:|:--------------------:|:-----------------:|:-------------:|:-----------------:|:--------------:|:----------:|:-----------------:|:--------------:|:----------:|:-----------------------:|:--------------------:|:----------------:|:-----------------------:|:--------------------:|:----------------:|:------------------:|:---------------:|:-----------:|:------------------:|:---------------:|:-----------:|:-------------------------:|:----------------------:|:------------------:|:-------------------------:|:----------------------:|:------------------:|:-------------------:|:----------------:|:------------:|:-------------------:|:----------------:|:------------:|:---------------------:|:------------------:|:--------------:|:------------------:|:-----------------------:|:--------------------:|:----------------:|:--------------------:|:---------------:|:------------:|:--------:|:------------:|:------------------:|:---------------:|:-----------:|:---------------:|:----------------:|:-------------:|:---------:|:-------------:|:-----------------:|:--------------:|:----------:|:--------------:|
| No log        | 1.0   | 425  | 0.1275          | 0.5171    | 0.3838 | 0.4406 | 0.9687   | nan                  | nan               | nan           | nan                  | nan               | nan           | nan               | nan            | nan        | nan               | nan            | nan        | nan                     | nan                  | nan              | nan                     | nan                  | nan              | nan                | nan             | nan         | nan                | nan             | nan         | nan                       | nan                    | nan                | nan                       | nan                    | nan                | nan                 | nan              | nan          | nan                 | nan              | nan          | 0.0                   | 0.0                | 0.0            | 221                | 0.0                     | 0.0                  | 0.0              | 140                  | 0.0             | 0.0          | 0.0      | 264          | 0.4054             | 0.4690          | 0.4349      | 548             | 0.6234           | 0.7348        | 0.6745    | 660           | 0.2963            | 0.1127         | 0.1633     | 142            |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cpu
- Datasets 2.14.6
- Tokenizers 0.14.1