---
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: 0.9943
- Accuracy: 0.5822
- F1 Score: 0.5820

## 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: 1.0136026165598675e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
| No log        | 1.0   | 186  | 1.1631          | 0.4636   | 0.4346   |
| No log        | 2.0   | 372  | 1.0563          | 0.5553   | 0.5558   |
| 1.1271        | 3.0   | 558  | 1.0238          | 0.5633   | 0.5629   |
| 1.1271        | 4.0   | 744  | 0.9990          | 0.5795   | 0.5786   |
| 1.1271        | 5.0   | 930  | 0.9943          | 0.5822   | 0.5820   |
| 0.8392        | 6.0   | 1116 | 1.0389          | 0.5741   | 0.5692   |
| 0.8392        | 7.0   | 1302 | 1.0114          | 0.5768   | 0.5759   |
| 0.8392        | 8.0   | 1488 | 1.0277          | 0.5741   | 0.5702   |
| 0.692         | 9.0   | 1674 | 1.0246          | 0.5822   | 0.5799   |
| 0.692         | 10.0  | 1860 | 1.0241          | 0.5822   | 0.5797   |


### Framework versions

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