---
base_model: ''
tags:
- generated_from_trainer
datasets:
- conll2003
model-index:
- name: span-marker-roberta-base-conll03
  results: []
---

<!-- 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. -->

# span-marker-roberta-base-conll03

This model is a fine-tuned version of [](https://huggingface.co/) on the conll2003 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0121
- Overall Precision: 0.9357
- Overall Recall: 0.9346
- Overall F1: 0.9351
- Overall Accuracy: 0.9870

## 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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|
| 0.0351        | 0.28  | 500  | 0.0272          | 0.8928            | 0.8251         | 0.8576     | 0.9662           |
| 0.0209        | 0.55  | 1000 | 0.0168          | 0.9066            | 0.9167         | 0.9116     | 0.9820           |
| 0.0169        | 0.83  | 1500 | 0.0120          | 0.9380            | 0.9291         | 0.9336     | 0.9863           |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3