---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-mc-5
  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-5

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4494
- Accuracy: 0.89

## 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: 60

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5837        | 1.0   | 25   | 1.5556          | 0.53     |
| 1.5523        | 2.0   | 50   | 1.5001          | 0.51     |
| 1.555         | 3.0   | 75   | 1.4666          | 0.48     |
| 1.4895        | 4.0   | 100  | 1.4224          | 0.49     |
| 1.4951        | 5.0   | 125  | 1.3924          | 0.495    |
| 1.4549        | 6.0   | 150  | 1.3716          | 0.53     |
| 1.4462        | 7.0   | 175  | 1.3372          | 0.51     |
| 1.4262        | 8.0   | 200  | 1.3005          | 0.515    |
| 1.3729        | 9.0   | 225  | 1.2497          | 0.525    |
| 1.4031        | 10.0  | 250  | 1.2854          | 0.535    |
| 1.3962        | 11.0  | 275  | 1.2891          | 0.56     |
| 1.3519        | 12.0  | 300  | 1.2060          | 0.53     |
| 1.362         | 13.0  | 325  | 1.3458          | 0.555    |
| 1.3693        | 14.0  | 350  | 1.1796          | 0.56     |
| 1.346         | 15.0  | 375  | 1.1360          | 0.585    |
| 1.2285        | 16.0  | 400  | 1.0907          | 0.57     |
| 1.2481        | 17.0  | 425  | 1.1393          | 0.56     |
| 1.2568        | 18.0  | 450  | 1.0404          | 0.6      |
| 1.2249        | 19.0  | 475  | 1.0012          | 0.595    |
| 1.1611        | 20.0  | 500  | 1.0123          | 0.615    |
| 1.1416        | 21.0  | 525  | 0.9631          | 0.64     |
| 1.2197        | 22.0  | 550  | 1.0537          | 0.625    |
| 1.2029        | 23.0  | 575  | 0.9518          | 0.66     |
| 1.1971        | 24.0  | 600  | 0.9295          | 0.67     |
| 1.1513        | 25.0  | 625  | 0.9045          | 0.675    |
| 1.0185        | 26.0  | 650  | 0.8620          | 0.71     |
| 1.1352        | 27.0  | 675  | 1.0548          | 0.69     |
| 1.1593        | 28.0  | 700  | 1.0043          | 0.68     |
| 1.1418        | 29.0  | 725  | 0.8569          | 0.7      |
| 1.0534        | 30.0  | 750  | 0.8284          | 0.715    |
| 1.08          | 31.0  | 775  | 0.7953          | 0.73     |
| 1.0148        | 32.0  | 800  | 0.7775          | 0.74     |
| 1.0526        | 33.0  | 825  | 0.8120          | 0.755    |
| 1.03          | 34.0  | 850  | 0.7630          | 0.76     |
| 1.0287        | 35.0  | 875  | 0.7651          | 0.745    |
| 1.0287        | 36.0  | 900  | 0.7174          | 0.765    |
| 0.9901        | 37.0  | 925  | 0.7268          | 0.75     |
| 0.9257        | 38.0  | 950  | 0.7114          | 0.765    |
| 0.9372        | 39.0  | 975  | 0.6691          | 0.805    |
| 0.9582        | 40.0  | 1000 | 0.6650          | 0.795    |
| 0.8728        | 41.0  | 1025 | 0.6588          | 0.78     |
| 0.8925        | 42.0  | 1050 | 0.6426          | 0.81     |
| 0.9357        | 43.0  | 1075 | 0.6302          | 0.815    |
| 0.9257        | 44.0  | 1100 | 0.7645          | 0.795    |
| 0.8763        | 45.0  | 1125 | 0.6034          | 0.815    |
| 0.838         | 46.0  | 1150 | 0.5711          | 0.815    |
| 0.8652        | 47.0  | 1175 | 0.5583          | 0.83     |
| 0.8106        | 48.0  | 1200 | 0.5560          | 0.835    |
| 0.8567        | 49.0  | 1225 | 0.5361          | 0.825    |
| 0.8185        | 50.0  | 1250 | 0.5926          | 0.825    |
| 0.8327        | 51.0  | 1275 | 0.5550          | 0.85     |
| 0.7822        | 52.0  | 1300 | 0.5193          | 0.85     |
| 0.7971        | 53.0  | 1325 | 0.5213          | 0.85     |
| 0.8051        | 54.0  | 1350 | 0.5175          | 0.845    |
| 0.7815        | 55.0  | 1375 | 0.4801          | 0.885    |
| 0.7391        | 56.0  | 1400 | 0.5759          | 0.87     |
| 0.8168        | 57.0  | 1425 | 0.4646          | 0.88     |
| 0.6991        | 58.0  | 1450 | 0.4713          | 0.885    |
| 0.7545        | 59.0  | 1475 | 0.4882          | 0.885    |
| 0.7222        | 60.0  | 1500 | 0.4494          | 0.89     |


### Framework versions

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