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

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: 0.0158
- 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   | 0.6785          | 0.74     | 0.7413 |
| No log        | 0.01  | 100  | 0.6047          | 0.79     | 0.7903 |
| No log        | 0.01  | 150  | 0.4424          | 0.88     | 0.8769 |
| No log        | 0.02  | 200  | 0.3601          | 0.89     | 0.8868 |
| No log        | 0.02  | 250  | 0.3436          | 0.89     | 0.8868 |
| No log        | 0.03  | 300  | 0.3311          | 0.9      | 0.8975 |
| No log        | 0.03  | 350  | 0.3145          | 0.89     | 0.8876 |
| No log        | 0.04  | 400  | 0.3113          | 0.9      | 0.8982 |
| No log        | 0.04  | 450  | 0.2994          | 0.9      | 0.8982 |
| 0.4886        | 0.05  | 500  | 0.2806          | 0.88     | 0.8785 |
| 0.4886        | 0.05  | 550  | 0.2179          | 0.92     | 0.9194 |
| 0.4886        | 0.06  | 600  | 0.2388          | 0.88     | 0.8803 |
| 0.4886        | 0.06  | 650  | 0.1716          | 0.94     | 0.9398 |
| 0.4886        | 0.07  | 700  | 0.1774          | 0.93     | 0.9302 |
| 0.4886        | 0.07  | 750  | 0.1456          | 0.95     | 0.9501 |
| 0.4886        | 0.08  | 800  | 0.1518          | 0.94     | 0.9402 |
| 0.4886        | 0.08  | 850  | 0.1564          | 0.93     | 0.9303 |
| 0.4886        | 0.09  | 900  | 0.1684          | 0.92     | 0.9204 |
| 0.4886        | 0.09  | 950  | 0.1372          | 0.96     | 0.9602 |
| 0.2446        | 0.1   | 1000 | 0.1368          | 0.94     | 0.9402 |
| 0.2446        | 0.1   | 1050 | 0.1502          | 0.95     | 0.9502 |
| 0.2446        | 0.11  | 1100 | 0.1385          | 0.95     | 0.9502 |
| 0.2446        | 0.11  | 1150 | 0.1297          | 0.96     | 0.9602 |
| 0.2446        | 0.12  | 1200 | 0.1917          | 0.95     | 0.9502 |
| 0.2446        | 0.12  | 1250 | 0.1042          | 0.97     | 0.9700 |
| 0.2446        | 0.13  | 1300 | 0.1502          | 0.96     | 0.9602 |
| 0.2446        | 0.13  | 1350 | 0.1436          | 0.96     | 0.9602 |
| 0.2446        | 0.14  | 1400 | 0.0896          | 0.98     | 0.9800 |
| 0.2446        | 0.14  | 1450 | 0.1045          | 0.96     | 0.9602 |
| 0.1824        | 0.15  | 1500 | 0.1269          | 0.96     | 0.9602 |
| 0.1824        | 0.15  | 1550 | 0.1449          | 0.96     | 0.9602 |
| 0.1824        | 0.16  | 1600 | 0.1311          | 0.96     | 0.9602 |
| 0.1824        | 0.16  | 1650 | 0.1380          | 0.96     | 0.9602 |
| 0.1824        | 0.17  | 1700 | 0.1466          | 0.96     | 0.9602 |
| 0.1824        | 0.17  | 1750 | 0.0861          | 0.98     | 0.9800 |
| 0.1824        | 0.18  | 1800 | 0.1323          | 0.96     | 0.9602 |
| 0.1824        | 0.18  | 1850 | 0.1375          | 0.96     | 0.9602 |
| 0.1824        | 0.19  | 1900 | 0.1719          | 0.96     | 0.9602 |
| 0.1824        | 0.19  | 1950 | 0.0837          | 0.98     | 0.9800 |
| 0.1252        | 0.2   | 2000 | 0.1661          | 0.96     | 0.9602 |
| 0.1252        | 0.2   | 2050 | 0.1129          | 0.96     | 0.9602 |
| 0.1252        | 0.21  | 2100 | 0.0603          | 0.98     | 0.9800 |
| 0.1252        | 0.21  | 2150 | 0.1231          | 0.96     | 0.9602 |
| 0.1252        | 0.22  | 2200 | 0.1363          | 0.96     | 0.9602 |
| 0.1252        | 0.22  | 2250 | 0.1330          | 0.96     | 0.9602 |
| 0.1252        | 0.23  | 2300 | 0.0795          | 0.96     | 0.9602 |
| 0.1252        | 0.23  | 2350 | 0.0856          | 0.96     | 0.9602 |


### Framework versions

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