---
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-base-multilingual-cased-ner-hrl
  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-multilingual-cased-ner-hrl

This model was finetuned on conll2003 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0799
- Precision: 0.9432
- Recall: 0.9549
- F1: 0.9490
- Accuracy: 0.9870

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0309        | 1.0   | 1756 | 0.0834          | 0.9307    | 0.9472 | 0.9389 | 0.9851   |
| 0.0157        | 2.0   | 3512 | 0.0784          | 0.9437    | 0.9536 | 0.9486 | 0.9873   |
| 0.0094        | 3.0   | 5268 | 0.0799          | 0.9432    | 0.9549 | 0.9490 | 0.9870   |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.0.0+cpu
- Datasets 2.18.0
- Tokenizers 0.15.2