---
license: mit
base_model: prajjwal1/bert-tiny
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: INT03
  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. -->

# INT03

This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0169
- Accuracy: 1.0
- F1: 1.0

## 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: 5e-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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 0.0   | 50   | 0.6888          | 0.62     | 0.5657 |
| No log        | 0.01  | 100  | 0.6817          | 0.66     | 0.5965 |
| No log        | 0.01  | 150  | 0.6004          | 0.86     | 0.8553 |
| No log        | 0.02  | 200  | 0.4136          | 0.87     | 0.8651 |
| No log        | 0.02  | 250  | 0.3550          | 0.89     | 0.8889 |
| No log        | 0.03  | 300  | 0.3241          | 0.89     | 0.8889 |
| No log        | 0.03  | 350  | 0.3144          | 0.89     | 0.8889 |
| No log        | 0.04  | 400  | 0.3146          | 0.89     | 0.8889 |
| No log        | 0.04  | 450  | 0.2985          | 0.89     | 0.8889 |
| 0.5219        | 0.05  | 500  | 0.2604          | 0.92     | 0.92   |
| 0.5219        | 0.05  | 550  | 0.2242          | 0.92     | 0.9202 |
| 0.5219        | 0.06  | 600  | 0.1976          | 0.92     | 0.9197 |
| 0.5219        | 0.06  | 650  | 0.1800          | 0.93     | 0.9302 |
| 0.5219        | 0.07  | 700  | 0.1685          | 0.93     | 0.9302 |
| 0.5219        | 0.07  | 750  | 0.1706          | 0.93     | 0.9303 |
| 0.5219        | 0.08  | 800  | 0.1532          | 0.93     | 0.9303 |
| 0.5219        | 0.08  | 850  | 0.1411          | 0.93     | 0.9303 |
| 0.5219        | 0.09  | 900  | 0.1070          | 0.98     | 0.9799 |
| 0.5219        | 0.09  | 950  | 0.0970          | 0.96     | 0.9601 |
| 0.2869        | 0.1   | 1000 | 0.0775          | 0.96     | 0.9601 |
| 0.2869        | 0.1   | 1050 | 0.0789          | 0.97     | 0.9701 |
| 0.2869        | 0.11  | 1100 | 0.0546          | 0.98     | 0.98   |
| 0.2869        | 0.11  | 1150 | 0.0789          | 0.98     | 0.9800 |
| 0.2869        | 0.12  | 1200 | 0.0425          | 0.99     | 0.9900 |
| 0.2869        | 0.12  | 1250 | 0.0443          | 0.99     | 0.9900 |
| 0.2869        | 0.13  | 1300 | 0.0340          | 0.99     | 0.9900 |
| 0.2869        | 0.13  | 1350 | 0.0649          | 0.97     | 0.9700 |
| 0.2869        | 0.14  | 1400 | 0.0241          | 1.0      | 1.0    |
| 0.2869        | 0.14  | 1450 | 0.0215          | 1.0      | 1.0    |
| 0.1754        | 0.15  | 1500 | 0.0146          | 1.0      | 1.0    |
| 0.1754        | 0.15  | 1550 | 0.0125          | 1.0      | 1.0    |
| 0.1754        | 0.16  | 1600 | 0.0122          | 1.0      | 1.0    |
| 0.1754        | 0.16  | 1650 | 0.0110          | 1.0      | 1.0    |
| 0.1754        | 0.17  | 1700 | 0.0092          | 1.0      | 1.0    |
| 0.1754        | 0.17  | 1750 | 0.0117          | 1.0      | 1.0    |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0