---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- ner
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: my_awesome_wnut_model
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: ner
      type: ner
      config: indian_names
      split: test
      args: indian_names
    metrics:
    - name: Precision
      type: precision
      value: 1.0
    - name: Recall
      type: recall
      value: 1.0
    - name: F1
      type: f1
      value: 1.0
    - name: Accuracy
      type: accuracy
      value: 1.0
---

<!-- 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. -->

# my_awesome_wnut_model

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co./bert-base-cased) on the ner dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0000
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 1.0

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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   | 344  | 0.0003          | 1.0000    | 1.0000 | 1.0000 | 1.0000   |
| 0.031         | 2.0   | 688  | 0.0002          | 1.0000    | 1.0000 | 1.0000 | 1.0000   |
| 0.005         | 3.0   | 1032 | 0.0000          | 1.0       | 1.0    | 1.0    | 1.0      |
| 0.005         | 4.0   | 1376 | 0.0000          | 1.0       | 1.0    | 1.0    | 1.0      |
| 0.001         | 5.0   | 1720 | 0.0000          | 1.0       | 1.0    | 1.0    | 1.0      |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3