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

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: 0.0603
- Accuracy: 0.9888
- Precision: 0.9864
- Recall: 0.9926

## 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: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy | Precision | Recall |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:---------:|:------:|
| 0.0499        | 1.0   | 32322  | 0.0552          | 0.9845   | 0.9883    | 0.9823 |
| 0.0453        | 2.0   | 64644  | 0.0563          | 0.9876   | 0.9843    | 0.9924 |
| 0.0361        | 3.0   | 96966  | 0.0596          | 0.9885   | 0.9884    | 0.9900 |
| 0.0254        | 4.0   | 129288 | 0.0603          | 0.9888   | 0.9864    | 0.9926 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1