---
license: mit
tags:
- generated_from_trainer
datasets:
- conll2003
metrics:
- precision
- recall
- f1
- accuracy
base_model: roberta-base
model-index:
- name: roberta-base-conll2003-pos
  results:
  - task:
      type: token-classification
      name: Token Classification
    dataset:
      name: conll2003
      type: conll2003
      args: conll2003
    metrics:
    - type: precision
      value: 0.9308159300631375
      name: Precision
    - type: recall
      value: 0.9300254761615917
      name: Recall
    - type: f1
      value: 0.9304205352266521
      name: F1
    - type: accuracy
      value: 0.9523967135236167
      name: Accuracy
---

<!-- 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. -->

# roberta-base-conll2003-pos

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the conll2003 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1947
- Precision: 0.9308
- Recall: 0.9300
- F1: 0.9304
- Accuracy: 0.9524

## 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: 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: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.617         | 1.0   | 878  | 0.2189          | 0.9239    | 0.9210 | 0.9225 | 0.9470   |
| 0.1667        | 2.0   | 1756 | 0.1947          | 0.9308    | 0.9300 | 0.9304 | 0.9524   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.14.0.dev20221107
- Datasets 2.2.2
- Tokenizers 0.12.1