---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta_multiple_choice
  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. -->

# roberta_multiple_choice

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1836
- Accuracy: 0.955

## 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: 5e-06
- 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: 100

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.4783        | 1.0   | 1725  | 1.3350          | 0.405    |
| 1.3252        | 2.0   | 3450  | 1.1893          | 0.565    |
| 1.2436        | 3.0   | 5175  | 1.0734          | 0.57     |
| 1.1636        | 4.0   | 6900  | 0.9469          | 0.61     |
| 1.0818        | 5.0   | 8625  | 0.8554          | 0.675    |
| 0.9999        | 6.0   | 10350 | 0.7437          | 0.715    |
| 0.9227        | 7.0   | 12075 | 0.6424          | 0.76     |
| 0.8361        | 8.0   | 13800 | 0.5657          | 0.8      |
| 0.7636        | 9.0   | 15525 | 0.5241          | 0.815    |
| 0.696         | 10.0  | 17250 | 0.4742          | 0.83     |
| 0.6343        | 11.0  | 18975 | 0.4325          | 0.855    |
| 0.5758        | 12.0  | 20700 | 0.4263          | 0.86     |
| 0.5377        | 13.0  | 22425 | 0.3876          | 0.835    |
| 0.4889        | 14.0  | 24150 | 0.3675          | 0.87     |
| 0.4467        | 15.0  | 25875 | 0.3221          | 0.885    |
| 0.4172        | 16.0  | 27600 | 0.3175          | 0.89     |
| 0.3899        | 17.0  | 29325 | 0.3048          | 0.9      |
| 0.3649        | 18.0  | 31050 | 0.2795          | 0.91     |
| 0.3413        | 19.0  | 32775 | 0.2669          | 0.905    |
| 0.3219        | 20.0  | 34500 | 0.2764          | 0.92     |
| 0.3055        | 21.0  | 36225 | 0.2478          | 0.93     |
| 0.2826        | 22.0  | 37950 | 0.2069          | 0.94     |
| 0.2733        | 23.0  | 39675 | 0.2230          | 0.945    |
| 0.2537        | 24.0  | 41400 | 0.2138          | 0.945    |
| 0.2412        | 25.0  | 43125 | 0.1887          | 0.95     |
| 0.2281        | 26.0  | 44850 | 0.1923          | 0.955    |
| 0.2188        | 27.0  | 46575 | 0.1663          | 0.96     |
| 0.2031        | 28.0  | 48300 | 0.2389          | 0.945    |
| 0.2008        | 29.0  | 50025 | 0.1823          | 0.955    |
| 0.1858        | 30.0  | 51750 | 0.1994          | 0.95     |
| 0.1854        | 31.0  | 53475 | 0.2013          | 0.96     |
| 0.1721        | 32.0  | 55200 | 0.1836          | 0.955    |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3