---
license: mit
base_model: Mikask/bdc2024-tpg
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: bdc2024-tpg-2
  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-2

This model is a fine-tuned version of [Mikask/bdc2024-tpg](https://huggingface.co/Mikask/bdc2024-tpg) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0953
- Accuracy: 0.9825
- Balanced Accuracy: 0.9863
- 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: 6e-06
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:---------:|:------:|:------:|
| 0.0781        | 1.0   | 900  | 0.0990          | 0.9803   | 0.9779            | 0.9810    | 0.9803 | 0.9804 |
| 0.0228        | 2.0   | 1800 | 0.0925          | 0.9782   | 0.9752            | 0.9788    | 0.9782 | 0.9782 |
| 0.017         | 3.0   | 2700 | 0.0953          | 0.9825   | 0.9863            | 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