README.md

---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ner-multilingual-bert
  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. -->

# ner-multilingual-bert

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0002
- Precision: 0.9998
- Recall: 0.9991
- F1: 0.9994
- Accuracy: 1.0000

## Model description

Trained to detect author and publish dates out of text beginnings

## Intended uses & limitations

More information needed

## Training and evaluation data

See [Dataset](https://huggingface.co/datasets/textminr/ner_tokenized)

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0108        | 0.2   | 250  | 0.0039          | 0.9942    | 0.9818 | 0.9880 | 0.9992   |
| 0.0022        | 0.4   | 500  | 0.0021          | 0.9863    | 0.9861 | 0.9862 | 0.9993   |
| 0.0006        | 0.61  | 750  | 0.0007          | 0.9998    | 0.9975 | 0.9986 | 0.9999   |
| 0.0004        | 0.81  | 1000 | 0.0002          | 0.9998    | 0.9991 | 0.9994 | 1.0000   |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0