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---
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
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