---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- mlner2021
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: mlner-mlwptok-muril
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: mlner2021
      type: mlner2021
      args: MLNER2021
    metrics:
    - name: Precision
      type: precision
      value: 0.0
    - name: Recall
      type: recall
      value: 0.0
    - name: F1
      type: f1
      value: 0.0
    - name: Accuracy
      type: accuracy
      value: 0.8112759262826688
---

<!-- 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. -->

# mlner-mlwptok-muril

This model is a fine-tuned version of [google/muril-base-cased](https://huggingface.co/google/muril-base-cased) on the mlner2021 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8331
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.8113

## 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1  | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:---:|:--------:|
| 1.447         | 1.0   | 1389  | 0.9396          | 0.0       | 0.0    | 0.0 | 0.8113   |
| 0.898         | 2.0   | 2778  | 0.8883          | 0.0       | 0.0    | 0.0 | 0.8113   |
| 0.859         | 3.0   | 4167  | 0.8721          | 0.0       | 0.0    | 0.0 | 0.8113   |
| 0.8302        | 4.0   | 5556  | 0.8666          | 0.0       | 0.0    | 0.0 | 0.8113   |
| 0.8165        | 5.0   | 6945  | 0.8403          | 0.0       | 0.0    | 0.0 | 0.8113   |
| 0.8143        | 6.0   | 8334  | 0.8376          | 0.0       | 0.0    | 0.0 | 0.8113   |
| 0.8034        | 7.0   | 9723  | 0.8393          | 0.0       | 0.0    | 0.0 | 0.8113   |
| 0.7766        | 8.0   | 11112 | 0.8383          | 0.0       | 0.0    | 0.0 | 0.8113   |
| 0.794         | 9.0   | 12501 | 0.8346          | 0.0       | 0.0    | 0.0 | 0.8113   |
| 0.7858        | 10.0  | 13890 | 0.8331          | 0.0       | 0.0    | 0.0 | 0.8113   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6