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

# finetuned_bert-base-uncased

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: 1.0293
- Accuracy: 0.6664

## 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: 2e-05
- 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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 204  | 1.0807          | 0.6586   |
| No log        | 2.0   | 408  | 1.2250          | 0.6760   |
| 0.271         | 3.0   | 612  | 1.1975          | 0.6663   |
| 0.271         | 4.0   | 816  | 1.2170          | 0.6625   |
| 0.2395        | 5.0   | 1020 | 1.2817          | 0.6702   |
| 0.2395        | 6.0   | 1224 | 1.4138          | 0.6634   |
| 0.2395        | 7.0   | 1428 | 1.5268          | 0.6819   |
| 0.1661        | 8.0   | 1632 | 1.5753          | 0.6702   |
| 0.1661        | 9.0   | 1836 | 1.6794          | 0.6663   |
| 0.1349        | 10.0  | 2040 | 1.6416          | 0.6731   |
| 0.1349        | 11.0  | 2244 | 1.7056          | 0.6741   |
| 0.1349        | 12.0  | 2448 | 1.7374          | 0.6760   |
| 0.1159        | 13.0  | 2652 | 1.8817          | 0.6644   |
| 0.1159        | 14.0  | 2856 | 1.7318          | 0.6751   |
| 0.111         | 15.0  | 3060 | 1.8213          | 0.6712   |
| 0.111         | 16.0  | 3264 | 1.8347          | 0.6722   |
| 0.111         | 17.0  | 3468 | 1.8072          | 0.6780   |
| 0.0988        | 18.0  | 3672 | 1.8371          | 0.6770   |
| 0.0988        | 19.0  | 3876 | 1.8562          | 0.6741   |
| 0.0907        | 20.0  | 4080 | 1.8583          | 0.6741   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2