---
license: mit
base_model: prajjwal1/bert-small
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-small-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

This model is a fine-tuned version of [prajjwal1/bert-small](https://huggingface.co/prajjwal1/bert-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0048
- Accuracy: 0.6038
- F1 Score: 0.6018

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| 1.3167        | 1.0   | 18   | 1.2414          | 0.4151   | 0.3857   |
| 1.1845        | 2.0   | 36   | 1.1500          | 0.5148   | 0.5148   |
| 1.0823        | 3.0   | 54   | 1.0743          | 0.5499   | 0.5543   |
| 0.995         | 4.0   | 72   | 1.0359          | 0.5553   | 0.5529   |
| 0.9242        | 5.0   | 90   | 1.0195          | 0.5849   | 0.5781   |
| 0.8742        | 6.0   | 108  | 1.0028          | 0.5741   | 0.5758   |
| 0.8237        | 7.0   | 126  | 1.0033          | 0.5930   | 0.5901   |
| 0.7893        | 8.0   | 144  | 0.9967          | 0.5930   | 0.5922   |
| 0.7332        | 9.0   | 162  | 1.0088          | 0.5957   | 0.5924   |
| 0.6997        | 10.0  | 180  | 1.0048          | 0.6038   | 0.6018   |
| 0.6836        | 11.0  | 198  | 1.0120          | 0.6011   | 0.5981   |
| 0.6571        | 12.0  | 216  | 1.0084          | 0.5849   | 0.5864   |
| 0.6253        | 13.0  | 234  | 1.0167          | 0.5903   | 0.5938   |
| 0.5902        | 14.0  | 252  | 1.0184          | 0.5930   | 0.5965   |
| 0.5766        | 15.0  | 270  | 1.0340          | 0.5930   | 0.5925   |
| 0.5591        | 16.0  | 288  | 1.0399          | 0.5930   | 0.5931   |
| 0.5353        | 17.0  | 306  | 1.0364          | 0.5930   | 0.5944   |
| 0.5205        | 18.0  | 324  | 1.0412          | 0.5876   | 0.5889   |
| 0.5197        | 19.0  | 342  | 1.0410          | 0.5849   | 0.5867   |
| 0.5222        | 20.0  | 360  | 1.0418          | 0.5984   | 0.5990   |


### Framework versions

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