---
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: 2.8732
- Accuracy: 0.4263

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.7365        | 1.0   | 502   | 1.5167          | 0.4288   |
| 1.3495        | 2.0   | 1004  | 1.4797          | 0.4592   |
| 1.1131        | 3.0   | 1506  | 1.5093          | 0.4527   |
| 0.9213        | 4.0   | 2008  | 1.6501          | 0.4522   |
| 0.7787        | 5.0   | 2510  | 1.7494          | 0.4407   |
| 0.6594        | 6.0   | 3012  | 1.8600          | 0.4417   |
| 0.5807        | 7.0   | 3514  | 1.9974          | 0.4412   |
| 0.5142        | 8.0   | 4016  | 2.0887          | 0.4273   |
| 0.4716        | 9.0   | 4518  | 2.1556          | 0.4273   |
| 0.4364        | 10.0  | 5020  | 2.2847          | 0.4348   |
| 0.3934        | 11.0  | 5522  | 2.3842          | 0.4298   |
| 0.3774        | 12.0  | 6024  | 2.4663          | 0.4228   |
| 0.3498        | 13.0  | 6526  | 2.5637          | 0.4253   |
| 0.337         | 14.0  | 7028  | 2.6162          | 0.4273   |
| 0.3191        | 15.0  | 7530  | 2.6466          | 0.4268   |
| 0.3081        | 16.0  | 8032  | 2.6214          | 0.4288   |
| 0.2889        | 17.0  | 8534  | 2.8064          | 0.4258   |
| 0.2831        | 18.0  | 9036  | 2.8042          | 0.4228   |
| 0.2733        | 19.0  | 9538  | 2.8510          | 0.4288   |
| 0.2648        | 20.0  | 10040 | 2.8732          | 0.4263   |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2