---
license: mit
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: roberta-base-finetuned-paperconc5
  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. -->

# IRyS-NER-Paper

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on a paper dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1197
- Precision: 0.7812
- Recall: 0.7548
- F1: 0.7677
- Accuracy: 0.9686

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 81   | 0.1969          | 0.6799    | 0.5433 | 0.6040 | 0.9448   |
| No log        | 2.0   | 162  | 0.1423          | 0.7634    | 0.6617 | 0.7089 | 0.9623   |
| No log        | 3.0   | 243  | 0.1197          | 0.7812    | 0.7548 | 0.7677 | 0.9686   |
| No log        | 4.0   | 324  | 0.1335          | 0.7819    | 0.7505 | 0.7659 | 0.9678   |
| No log        | 5.0   | 405  | 0.1326          | 0.7345    | 0.8013 | 0.7664 | 0.9650   |
| No log        | 6.0   | 486  | 0.1427          | 0.7471    | 0.8182 | 0.7810 | 0.9657   |
| 0.1446        | 7.0   | 567  | 0.1439          | 0.7447    | 0.8203 | 0.7807 | 0.9666   |
| 0.1446        | 8.0   | 648  | 0.1586          | 0.7368    | 0.8288 | 0.7801 | 0.9650   |
| 0.1446        | 9.0   | 729  | 0.1707          | 0.7273    | 0.8288 | 0.7747 | 0.9629   |
| 0.1446        | 10.0  | 810  | 0.1650          | 0.7438    | 0.8288 | 0.784  | 0.9649   |


### Framework versions

- Transformers 4.27.2
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2