---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: patent-bert-classifier
  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. -->

# patent-bert-classifier

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: 0.9548
- Accuracy: 0.681
- F1: 0.6557
- Precision: 0.6499
- Recall: 0.681

## 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 1.0317        | 1.0   | 1563 | 0.9973          | 0.6568   | 0.6323 | 0.6319    | 0.6568 |
| 0.8575        | 2.0   | 3126 | 0.9251          | 0.6888   | 0.6641 | 0.6592    | 0.6888 |
| 0.6298        | 3.0   | 4689 | 0.9880          | 0.6736   | 0.6604 | 0.6533    | 0.6736 |
| 0.4886        | 4.0   | 6252 | 1.0900          | 0.6764   | 0.6678 | 0.6615    | 0.6764 |
| 0.3765        | 5.0   | 7815 | 1.1712          | 0.6688   | 0.6601 | 0.6545    | 0.6688 |


### Framework versions

- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.2.0
- Tokenizers 0.22.1