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# 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

{"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"}]}]}]}
transformers pytorch tensorboard roberta token-classification generated_from_trainer dataset:conll2003 base_model:roberta-base license:mit model-index autotrain_compatible endpoints_compatible region:us