---
library_name: transformers
license: apache-2.0
base_model: google/muril-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: muril-ner-multilingual-v2
  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. -->

# muril-ner-multilingual-v2

This model is a fine-tuned version of [google/muril-base-cased](https://huggingface.co/google/muril-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2213
- Precision: 0.7501
- Recall: 0.7872
- F1: 0.7682
- Accuracy: 0.9383

## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.2128        | 1.0   | 6250  | 0.2208          | 0.7484    | 0.7707 | 0.7594 | 0.9361   |
| 0.1840        | 2.0   | 12500 | 0.2173          | 0.7375    | 0.7950 | 0.7652 | 0.9366   |
| 0.1435        | 3.0   | 18750 | 0.2213          | 0.7501    | 0.7872 | 0.7682 | 0.9383   |


### Framework versions

- Transformers 5.14.1
- Pytorch 2.11.0+cu128
- Datasets 2.21.0
- Tokenizers 0.22.2