---
library_name: transformers
license: mit
base_model: simpliTax/bert-automap-pbt-fine-tuned
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: category-v7
  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-v7

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: 1.8340
- Accuracy: 0.6194
- Macro F1: 0.1932
- Weighted F1: 0.5556

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:|
| 3.9298        | 1.0   | 797  | 2.5314          | 0.5184   | 0.1309   | 0.4396      |
| 2.2155        | 2.0   | 1594 | 1.9882          | 0.6024   | 0.1807   | 0.5384      |
| 1.8729        | 3.0   | 2391 | 1.8340          | 0.6194   | 0.1932   | 0.5556      |


### Framework versions

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