---
license: mit
base_model: ryantaw/bert-small-finetuned
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-small-finetuned-finetuned
  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-small-finetuned-finetuned

This model is a fine-tuned version of [ryantaw/bert-small-finetuned](https://huggingface.co/ryantaw/bert-small-finetuned) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0767
- Accuracy: 0.6119
- F1 Score: 0.6156

## 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: 86
- eval_batch_size: 86
- 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 | F1 Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 0.7125        | 1.0   | 18   | 1.0136          | 0.6011   | 0.5997   |
| 0.604         | 2.0   | 36   | 1.0198          | 0.6038   | 0.6058   |
| 0.5421        | 3.0   | 54   | 1.0517          | 0.6065   | 0.6068   |
| 0.4724        | 4.0   | 72   | 1.0767          | 0.6119   | 0.6156   |
| 0.42          | 5.0   | 90   | 1.1184          | 0.5768   | 0.5751   |
| 0.3823        | 6.0   | 108  | 1.1217          | 0.5876   | 0.5881   |
| 0.3312        | 7.0   | 126  | 1.1425          | 0.6065   | 0.6053   |
| 0.3045        | 8.0   | 144  | 1.1760          | 0.6065   | 0.6095   |
| 0.2662        | 9.0   | 162  | 1.2044          | 0.6065   | 0.6090   |
| 0.2403        | 10.0  | 180  | 1.2143          | 0.6011   | 0.6011   |
| 0.2308        | 11.0  | 198  | 1.2394          | 0.5903   | 0.5927   |
| 0.2053        | 12.0  | 216  | 1.2589          | 0.6038   | 0.6068   |
| 0.1808        | 13.0  | 234  | 1.2895          | 0.6065   | 0.6071   |
| 0.1599        | 14.0  | 252  | 1.3144          | 0.6065   | 0.6086   |
| 0.1497        | 15.0  | 270  | 1.3386          | 0.5930   | 0.5951   |
| 0.1383        | 16.0  | 288  | 1.3608          | 0.5903   | 0.5931   |
| 0.1321        | 17.0  | 306  | 1.3624          | 0.5876   | 0.5888   |
| 0.1183        | 18.0  | 324  | 1.3810          | 0.5930   | 0.5945   |
| 0.1196        | 19.0  | 342  | 1.3827          | 0.5903   | 0.5927   |
| 0.1181        | 20.0  | 360  | 1.3805          | 0.5903   | 0.5920   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1