---
license: mit
base_model: roberta-large
tags:
- generated_from_trainer
datasets:
- open_question_type
metrics:
- f1
model-index:
- name: roberta-large-question-classifier
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: open_question_type
      type: open_question_type
      config: default
      split: validation
      args: default
    metrics:
    - name: F1
      type: f1
      value: 0.7954091951908298
---

<!-- 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-large-question-classifier

This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on the open_question_type dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9002
- F1: 0.7954

## 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: 512
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 1.9467        | 1.0   | 233  | 1.3099          | 0.4050 |
| 0.6381        | 2.0   | 466  | 0.5586          | 0.7785 |
| 0.628         | 3.0   | 699  | 0.6419          | 0.7831 |
| 0.4487        | 4.0   | 932  | 0.5770          | 0.8094 |
| 0.3319        | 5.0   | 1165 | 0.7713          | 0.7953 |
| 0.2095        | 6.0   | 1398 | 0.8799          | 0.8018 |
| 0.1355        | 7.0   | 1631 | 1.0646          | 0.7961 |
| 0.0956        | 8.0   | 1864 | 1.2175          | 0.7999 |
| 0.0687        | 9.0   | 2097 | 1.3647          | 0.7892 |
| 0.0371        | 10.0  | 2330 | 1.3809          | 0.7987 |
| 0.0303        | 11.0  | 2563 | 1.3591          | 0.8123 |
| 0.0263        | 12.0  | 2796 | 1.5317          | 0.8100 |
| 0.0144        | 13.0  | 3029 | 1.5726          | 0.7959 |
| 0.0436        | 14.0  | 3262 | 1.6160          | 0.7988 |
| 0.0048        | 15.0  | 3495 | 1.6826          | 0.7957 |
| 0.0001        | 16.0  | 3728 | 1.6913          | 0.7957 |
| 0.0001        | 17.0  | 3961 | 1.7076          | 0.7995 |
| 0.0034        | 18.0  | 4194 | 1.8018          | 0.7960 |
| 0.0228        | 19.0  | 4427 | 1.7457          | 0.7916 |
| 0.0083        | 20.0  | 4660 | 1.9279          | 0.7869 |
| 0.0001        | 21.0  | 4893 | 1.8367          | 0.7915 |
| 0.0003        | 22.0  | 5126 | 1.8620          | 0.7842 |
| 0.0002        | 23.0  | 5359 | 1.9192          | 0.7828 |
| 0.0           | 24.0  | 5592 | 1.9081          | 0.7927 |
| 0.0003        | 25.0  | 5825 | 1.9822          | 0.7813 |
| 0.0059        | 26.0  | 6058 | 1.8737          | 0.7954 |
| 0.0           | 27.0  | 6291 | 1.8793          | 0.7929 |
| 0.0           | 28.0  | 6524 | 1.8905          | 0.7940 |
| 0.0           | 29.0  | 6757 | 1.8971          | 0.7940 |
| 0.0002        | 30.0  | 6990 | 1.9002          | 0.7954 |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3