---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-mc-3
  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-3

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5988
- Accuracy: 0.3

## 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-07
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6111        | 1.0   | 24   | 1.6061          | 0.4      |
| 1.6003        | 2.0   | 48   | 1.6062          | 0.4      |
| 1.6049        | 3.0   | 72   | 1.6062          | 0.4      |
| 1.5936        | 4.0   | 96   | 1.6059          | 0.4      |
| 1.6073        | 5.0   | 120  | 1.6057          | 0.4      |
| 1.6001        | 6.0   | 144  | 1.6055          | 0.3      |
| 1.5925        | 7.0   | 168  | 1.6052          | 0.3      |
| 1.5971        | 8.0   | 192  | 1.6050          | 0.3      |
| 1.597         | 9.0   | 216  | 1.6047          | 0.3      |
| 1.5956        | 10.0  | 240  | 1.6042          | 0.3      |
| 1.5882        | 11.0  | 264  | 1.6036          | 0.3      |
| 1.5944        | 12.0  | 288  | 1.6034          | 0.3      |
| 1.5941        | 13.0  | 312  | 1.6032          | 0.3      |
| 1.5941        | 14.0  | 336  | 1.6029          | 0.3      |
| 1.5825        | 15.0  | 360  | 1.6024          | 0.3      |
| 1.5817        | 16.0  | 384  | 1.6019          | 0.3      |
| 1.5922        | 17.0  | 408  | 1.6014          | 0.3      |
| 1.5915        | 18.0  | 432  | 1.6011          | 0.3      |
| 1.5822        | 19.0  | 456  | 1.6007          | 0.3      |
| 1.5967        | 20.0  | 480  | 1.6001          | 0.3      |
| 1.5887        | 21.0  | 504  | 1.5999          | 0.3      |
| 1.5905        | 22.0  | 528  | 1.5997          | 0.3      |
| 1.5828        | 23.0  | 552  | 1.5994          | 0.3      |
| 1.5851        | 24.0  | 576  | 1.5992          | 0.3      |
| 1.5789        | 25.0  | 600  | 1.5991          | 0.3      |
| 1.5797        | 26.0  | 624  | 1.5990          | 0.3      |
| 1.5845        | 27.0  | 648  | 1.5989          | 0.3      |
| 1.5992        | 28.0  | 672  | 1.5988          | 0.3      |
| 1.5791        | 29.0  | 696  | 1.5988          | 0.3      |
| 1.5785        | 30.0  | 720  | 1.5988          | 0.3      |


### Framework versions

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