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---
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
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