---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert-base-uncased_LOGIC_Native
  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. -->

# bert-base-uncased_LOGIC_Native

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7437
- Accuracy: 0.61
- Macro Precision: 0.5758
- Macro F1: 0.5770

## 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: 42
- optimizer: Use OptimizerNames.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: 12

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro Precision | Macro F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:--------:|
| No log        | 1.0   | 116  | 2.3493          | 0.2433   | 0.3585          | 0.2208   |
| No log        | 2.0   | 232  | 1.9408          | 0.4267   | 0.4271          | 0.3717   |
| No log        | 3.0   | 348  | 1.6372          | 0.4733   | 0.4433          | 0.4383   |
| No log        | 4.0   | 464  | 1.5114          | 0.59     | 0.5677          | 0.5507   |
| 1.7294        | 5.0   | 580  | 1.4359          | 0.6      | 0.5738          | 0.5761   |
| 1.7294        | 6.0   | 696  | 1.4476          | 0.6133   | 0.5913          | 0.5806   |
| 1.7294        | 7.0   | 812  | 1.4863          | 0.6133   | 0.5784          | 0.5823   |
| 1.7294        | 8.0   | 928  | 1.5494          | 0.63     | 0.5924          | 0.5903   |
| 0.3290        | 9.0   | 1044 | 1.6099          | 0.61     | 0.5733          | 0.5776   |
| 0.3290        | 10.0  | 1160 | 1.6845          | 0.6167   | 0.5809          | 0.5817   |
| 0.3290        | 11.0  | 1276 | 1.7364          | 0.6233   | 0.5811          | 0.5848   |
| 0.3290        | 12.0  | 1392 | 1.7437          | 0.61     | 0.5758          | 0.5770   |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2