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

This model is a fine-tuned version of [prajjwal1/bert-mini](https://huggingface.co/prajjwal1/bert-mini) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0565
- Accuracy: 0.9873
- Precision: 0.9848
- Recall: 0.9912

## 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 |
|:-------------:|:-----:|:------:|:---------------:|:--------:|:---------:|:------:|
| 0.0644        | 1.0   | 32322  | 0.0633          | 0.9815   | 0.9832    | 0.9818 |
| 0.0579        | 2.0   | 64644  | 0.0572          | 0.9853   | 0.9818    | 0.9906 |
| 0.0485        | 3.0   | 96966  | 0.0564          | 0.9867   | 0.9859    | 0.9892 |
| 0.0439        | 4.0   | 129288 | 0.0565          | 0.9873   | 0.9848    | 0.9912 |


### Framework versions

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