---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-mc-6
  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-mc-6

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6310
- Accuracy: 0.95

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 60

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6594        | 1.0   | 23   | 0.6523          | 0.95     |
| 0.6979        | 2.0   | 46   | 0.6400          | 0.95     |
| 0.6407        | 3.0   | 69   | 0.6331          | 0.95     |
| 0.7082        | 4.0   | 92   | 0.6360          | 0.95     |
| 0.6493        | 5.0   | 115  | 0.6258          | 0.95     |
| 0.6827        | 6.0   | 138  | 0.6239          | 0.95     |
| 0.6511        | 7.0   | 161  | 0.6399          | 0.95     |
| 0.6459        | 8.0   | 184  | 0.6279          | 0.95     |
| 0.6623        | 9.0   | 207  | 0.6247          | 0.95     |
| 0.6583        | 10.0  | 230  | 0.6307          | 0.95     |
| 0.6613        | 11.0  | 253  | 0.6269          | 0.95     |
| 0.6223        | 12.0  | 276  | 0.6270          | 0.95     |
| 0.6375        | 13.0  | 299  | 0.6284          | 0.95     |
| 0.7009        | 14.0  | 322  | 0.6309          | 0.95     |
| 0.6705        | 15.0  | 345  | 0.6299          | 0.95     |
| 0.6503        | 16.0  | 368  | 0.6396          | 0.95     |
| 0.7073        | 17.0  | 391  | 0.6305          | 0.95     |
| 0.614         | 18.0  | 414  | 0.6308          | 0.95     |
| 0.6512        | 19.0  | 437  | 0.6305          | 0.95     |
| 0.7055        | 20.0  | 460  | 0.6308          | 0.95     |
| 0.5702        | 21.0  | 483  | 0.6304          | 0.95     |
| 0.6654        | 22.0  | 506  | 0.6305          | 0.95     |
| 0.6129        | 23.0  | 529  | 0.6308          | 0.95     |
| 0.6477        | 24.0  | 552  | 0.6310          | 0.95     |
| 0.6178        | 25.0  | 575  | 0.6312          | 0.95     |
| 0.6562        | 26.0  | 598  | 0.6312          | 0.95     |
| 0.5972        | 27.0  | 621  | 0.6317          | 0.95     |
| 0.6324        | 28.0  | 644  | 0.6312          | 0.95     |
| 0.6064        | 29.0  | 667  | 0.6312          | 0.95     |
| 0.5833        | 30.0  | 690  | 0.6312          | 0.95     |
| 0.6916        | 31.0  | 713  | 0.6312          | 0.95     |
| 0.5591        | 32.0  | 736  | 0.6312          | 0.95     |
| 0.6477        | 33.0  | 759  | 0.6312          | 0.95     |
| 0.6483        | 34.0  | 782  | 0.6311          | 0.95     |
| 0.5563        | 35.0  | 805  | 0.6310          | 0.95     |
| 0.6061        | 36.0  | 828  | 0.6310          | 0.95     |
| 0.6043        | 37.0  | 851  | 0.6310          | 0.95     |
| 0.6274        | 38.0  | 874  | 0.6310          | 0.95     |
| 0.6115        | 39.0  | 897  | 0.6310          | 0.95     |
| 0.7107        | 40.0  | 920  | 0.6310          | 0.95     |
| 0.6703        | 41.0  | 943  | 0.6310          | 0.95     |
| 0.6052        | 42.0  | 966  | 0.6310          | 0.95     |
| 0.6228        | 43.0  | 989  | 0.6310          | 0.95     |
| 0.6629        | 44.0  | 1012 | 0.6310          | 0.95     |
| 0.5804        | 45.0  | 1035 | 0.6310          | 0.95     |
| 0.6194        | 46.0  | 1058 | 0.6310          | 0.95     |
| 0.6529        | 47.0  | 1081 | 0.6310          | 0.95     |
| 0.5779        | 48.0  | 1104 | 0.6310          | 0.95     |
| 0.6652        | 49.0  | 1127 | 0.6310          | 0.95     |
| 0.6163        | 50.0  | 1150 | 0.6310          | 0.95     |
| 0.6873        | 51.0  | 1173 | 0.6310          | 0.95     |
| 0.5608        | 52.0  | 1196 | 0.6310          | 0.95     |
| 0.6646        | 53.0  | 1219 | 0.6310          | 0.95     |
| 0.6222        | 54.0  | 1242 | 0.6310          | 0.95     |
| 0.6629        | 55.0  | 1265 | 0.6310          | 0.95     |
| 0.592         | 56.0  | 1288 | 0.6310          | 0.95     |
| 0.6047        | 57.0  | 1311 | 0.6310          | 0.95     |
| 0.5668        | 58.0  | 1334 | 0.6310          | 0.95     |
| 0.6358        | 59.0  | 1357 | 0.6310          | 0.95     |
| 0.648         | 60.0  | 1380 | 0.6310          | 0.95     |


### Framework versions

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