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# uner-muril-ner

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: 0.1356
- Precision: 0.8055
- Recall: 0.8642
- F1: 0.8338
- Accuracy: 0.9637

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 144  | 0.1590          | 0.7660    | 0.7930 | 0.7793 | 0.9516   |
| No log        | 2.0   | 288  | 0.1321          | 0.7907    | 0.8625 | 0.8250 | 0.9593   |
| No log        | 3.0   | 432  | 0.1258          | 0.8002    | 0.8584 | 0.8283 | 0.9618   |
| 0.1493        | 4.0   | 576  | 0.1346          | 0.8009    | 0.8658 | 0.8321 | 0.9616   |
| 0.1493        | 5.0   | 720  | 0.1356          | 0.8055    | 0.8642 | 0.8338 | 0.9637   |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "bert-base-multilingual-cased", "model-index": [{"name": "uner-muril-ner", "results": []}]}
transformers pytorch bert token-classification generated_from_trainer base_model:bert-base-multilingual-cased license:apache-2.0 autotrain_compatible endpoints_compatible region:us