---
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: 0.9064
- Accuracy: 0.6591

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 204  | 0.9670          | 0.6052   |
| No log        | 2.0   | 408  | 0.8899          | 0.6731   |
| 0.8476        | 3.0   | 612  | 0.9283          | 0.6722   |
| 0.8476        | 4.0   | 816  | 1.0110          | 0.6828   |
| 0.3419        | 5.0   | 1020 | 1.0947          | 0.6741   |
| 0.3419        | 6.0   | 1224 | 1.1896          | 0.6799   |
| 0.3419        | 7.0   | 1428 | 1.3467          | 0.6887   |
| 0.193         | 8.0   | 1632 | 1.3716          | 0.6838   |
| 0.193         | 9.0   | 1836 | 1.4742          | 0.6809   |
| 0.1485        | 10.0  | 2040 | 1.5121          | 0.6867   |
| 0.1485        | 11.0  | 2244 | 1.5670          | 0.6819   |
| 0.1485        | 12.0  | 2448 | 1.5593          | 0.6867   |
| 0.1185        | 13.0  | 2652 | 1.6455          | 0.6809   |
| 0.1185        | 14.0  | 2856 | 1.6417          | 0.6877   |
| 0.1077        | 15.0  | 3060 | 1.6399          | 0.6867   |


### Framework versions

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