---
metrics:
- precision
- recall
- f1
- accuracy

model-index:
- name: test-ner
---

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# test-ner

This model was trained from scratch on an unkown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4357
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.8863

## 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: 0.02
- 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: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1  | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
| No log        | 1.0   | 340  | 0.4357          | 0.0       | 0.0    | 0.0 | 0.8863   |


### Framework versions

- Transformers 4.6.1
- Pytorch 1.9.0
- Datasets 1.6.2
- Tokenizers 0.10.3