---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-mc-4
  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-4

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4442
- Accuracy: 0.5

## 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: 0.001
- 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6061        | 1.0   | 24   | 1.5920          | 0.7      |
| 1.6032        | 2.0   | 48   | 1.5838          | 0.6      |
| 1.6104        | 3.0   | 72   | 1.5750          | 0.7      |
| 1.5851        | 4.0   | 96   | 1.5584          | 0.6      |
| 1.5653        | 5.0   | 120  | 1.5059          | 0.7      |
| 1.5485        | 6.0   | 144  | 1.4743          | 0.6      |
| 1.5175        | 7.0   | 168  | 1.4500          | 0.7      |
| 1.5025        | 8.0   | 192  | 1.4298          | 0.5      |
| 1.466         | 9.0   | 216  | 1.4559          | 0.5      |
| 1.4444        | 10.0  | 240  | 1.4010          | 0.5      |
| 1.4223        | 11.0  | 264  | 1.4699          | 0.4      |
| 1.3804        | 12.0  | 288  | 1.4915          | 0.4      |
| 1.3884        | 13.0  | 312  | 1.4624          | 0.4      |
| 1.3699        | 14.0  | 336  | 1.4798          | 0.5      |
| 1.3705        | 15.0  | 360  | 1.3615          | 0.5      |
| 1.3383        | 16.0  | 384  | 1.3814          | 0.7      |
| 1.3306        | 17.0  | 408  | 1.5099          | 0.4      |
| 1.2886        | 18.0  | 432  | 1.5039          | 0.4      |
| 1.2964        | 19.0  | 456  | 1.4033          | 0.5      |
| 1.285         | 20.0  | 480  | 1.4596          | 0.4      |
| 1.311         | 21.0  | 504  | 1.4100          | 0.4      |
| 1.218         | 22.0  | 528  | 1.3952          | 0.5      |
| 1.2193        | 23.0  | 552  | 1.2449          | 0.7      |
| 1.2618        | 24.0  | 576  | 1.2691          | 0.7      |
| 1.236         | 25.0  | 600  | 1.3427          | 0.7      |
| 1.1773        | 26.0  | 624  | 1.3669          | 0.5      |
| 1.1873        | 27.0  | 648  | 1.5114          | 0.5      |
| 1.1519        | 28.0  | 672  | 1.4285          | 0.6      |
| 1.1172        | 29.0  | 696  | 1.4485          | 0.5      |
| 1.0677        | 30.0  | 720  | 1.4442          | 0.5      |


### Framework versions

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