metadata
library_name: transformers
license: mit
base_model: simpliTax/bert-automap-pbt-fine-tuned
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: category-v6-strict
results: []
category-v6-strict
This model is a fine-tuned version of simpliTax/bert-automap-pbt-fine-tuned on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.9421
- Accuracy: 0.5960
- Macro F1: 0.1895
- Weighted F1: 0.5291
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 |
|---|---|---|---|---|---|---|
| 3.8728 | 1.0 | 727 | 2.5961 | 0.4930 | 0.1212 | 0.4187 |
| 2.6532 | 2.0 | 1454 | 2.0727 | 0.5728 | 0.1676 | 0.5043 |
| 1.8412 | 3.0 | 2181 | 1.9421 | 0.5960 | 0.1895 | 0.5291 |
Framework versions
- Transformers 5.0.0.dev0
- Pytorch 2.9.0+cu126
- Datasets 4.3.0
- Tokenizers 0.22.1