---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert_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. -->

# bert_multiple_choice

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4718
- Accuracy: 0.4

## 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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6321        | 1.0   | 12   | 1.5869          | 0.45     |
| 1.6206        | 2.0   | 24   | 1.5864          | 0.45     |
| 1.6088        | 3.0   | 36   | 1.5849          | 0.45     |
| 1.6098        | 4.0   | 48   | 1.5760          | 0.5      |
| 1.5938        | 5.0   | 60   | 1.5746          | 0.55     |
| 1.5811        | 6.0   | 72   | 1.5726          | 0.5      |
| 1.5968        | 7.0   | 84   | 1.5699          | 0.55     |
| 1.5521        | 8.0   | 96   | 1.5627          | 0.5      |
| 1.5438        | 9.0   | 108  | 1.5485          | 0.45     |
| 1.5605        | 10.0  | 120  | 1.5456          | 0.35     |
| 1.552         | 11.0  | 132  | 1.5448          | 0.35     |
| 1.5065        | 12.0  | 144  | 1.5466          | 0.5      |
| 1.5075        | 13.0  | 156  | 1.5490          | 0.45     |
| 1.4757        | 14.0  | 168  | 1.5412          | 0.4      |
| 1.4504        | 15.0  | 180  | 1.5292          | 0.45     |
| 1.3916        | 16.0  | 192  | 1.5161          | 0.3      |
| 1.4132        | 17.0  | 204  | 1.5146          | 0.35     |
| 1.3652        | 18.0  | 216  | 1.4985          | 0.35     |
| 1.3303        | 19.0  | 228  | 1.4864          | 0.35     |
| 1.3441        | 20.0  | 240  | 1.4845          | 0.4      |
| 1.3161        | 21.0  | 252  | 1.4953          | 0.35     |
| 1.3025        | 22.0  | 264  | 1.4689          | 0.4      |
| 1.2371        | 23.0  | 276  | 1.4582          | 0.4      |
| 1.2468        | 24.0  | 288  | 1.4523          | 0.4      |
| 1.2156        | 25.0  | 300  | 1.4673          | 0.45     |
| 1.1791        | 26.0  | 312  | 1.4608          | 0.4      |
| 1.1919        | 27.0  | 324  | 1.4125          | 0.4      |
| 1.1926        | 28.0  | 336  | 1.4655          | 0.45     |
| 1.1473        | 29.0  | 348  | 1.4629          | 0.4      |
| 1.1132        | 30.0  | 360  | 1.4481          | 0.4      |
| 1.1064        | 31.0  | 372  | 1.4754          | 0.4      |
| 1.1352        | 32.0  | 384  | 1.4718          | 0.4      |


### Framework versions

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