---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: page-extractor
  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. -->

# page-extractor

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1263
- Precision: 0.8683
- Recall: 0.8749
- F1: 0.8716
- Accuracy: 0.9649

## 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: 640
- eval_batch_size: 640
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 160  | 0.1194          | 0.8728    | 0.8633 | 0.8680 | 0.9650   |
| No log        | 2.0   | 320  | 0.1234          | 0.8705    | 0.8686 | 0.8695 | 0.9649   |
| No log        | 3.0   | 480  | 0.1263          | 0.8683    | 0.8749 | 0.8716 | 0.9649   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.3