---
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: bdc2024-tpg-3
  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. -->

# bdc2024-tpg-3

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1269
- Accuracy: 0.9825
- Balanced Accuracy: 0.9822
- Precision: 0.9832
- Recall: 0.9825
- F1: 0.9826

## 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: 1e-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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Balanced Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:---------:|:------:|:------:|
| 0.0142        | 1.0   | 900  | 0.1874          | 0.9782   | 0.9723            | 0.9789    | 0.9782 | 0.9782 |
| 0.0074        | 2.0   | 1800 | 0.1388          | 0.9782   | 0.9745            | 0.9793    | 0.9782 | 0.9783 |
| 0.0059        | 3.0   | 2700 | 0.1269          | 0.9825   | 0.9822            | 0.9832    | 0.9825 | 0.9826 |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.13.3