---
library_name: transformers
license: mit
base_model: simpliTax/bert-automap-pbt-fine-tuned
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: category-v6
  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. -->

# category-v6

This model is a fine-tuned version of [simpliTax/bert-automap-pbt-fine-tuned](https://huggingface.co/simpliTax/bert-automap-pbt-fine-tuned) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8371
- Accuracy: 0.6135
- Macro F1: 0.1923
- Weighted F1: 0.5567

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 13
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 | Weighted F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|
| 3.8596        | 1.0   | 752  | 2.5150          | 0.5139   | 0.1341   | 0.4412      |
| 2.1307        | 2.0   | 1504 | 1.9695          | 0.5903   | 0.1745   | 0.5248      |
| 1.7946        | 3.0   | 2256 | 1.8371          | 0.6135   | 0.1923   | 0.5567      |


### Framework versions

- Transformers 5.0.0.dev0
- Pytorch 2.9.0+cu126
- Datasets 4.3.0
- Tokenizers 0.22.1