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

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2046
- Accuracy: 0.52

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.413         | 1.0   | 75   | 1.3023          | 0.4667   |
| 1.2772        | 2.0   | 150  | 1.2043          | 0.52     |
| 1.2019        | 3.0   | 225  | 1.0879          | 0.5733   |
| 1.1463        | 4.0   | 300  | 1.1124          | 0.57     |
| 1.1566        | 5.0   | 375  | 1.1220          | 0.5367   |
| 1.1096        | 6.0   | 450  | 1.0675          | 0.5967   |
| 0.9806        | 7.0   | 525  | 1.0315          | 0.64     |
| 0.8715        | 8.0   | 600  | 1.0616          | 0.6      |
| 0.8788        | 9.0   | 675  | 1.1211          | 0.59     |
| 0.8071        | 10.0  | 750  | 1.1400          | 0.6      |
| 0.6908        | 11.0  | 825  | 1.1848          | 0.6033   |
| 0.6244        | 12.0  | 900  | 1.2255          | 0.59     |
| 0.628         | 13.0  | 975  | 1.2264          | 0.6      |
| 0.6003        | 14.0  | 1050 | 1.2270          | 0.6033   |
| 0.5283        | 15.0  | 1125 | 1.2399          | 0.5933   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1