---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wikiann
model-index:
- name: ner_marathi_bert
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# ner_marathi_bert

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the wikiann dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3606
- Overall Precision: 0.8939
- Overall Recall: 0.9030
- Overall F1: 0.8984
- Overall Accuracy: 0.9347
- Loc F1: 0.8823
- Org F1: 0.8555
- Per F1: 0.9435

## 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: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | Loc F1 | Org F1 | Per F1 |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:------:|:------:|:------:|
| 0.2961        | 3.19  | 1000 | 0.3496          | 0.8720            | 0.8841         | 0.8780     | 0.9229           | 0.8599 | 0.8210 | 0.9343 |
| 0.0613        | 6.39  | 2000 | 0.3606          | 0.8939            | 0.9030         | 0.8984     | 0.9347           | 0.8823 | 0.8555 | 0.9435 |


### Framework versions

- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1