---
license: apache-2.0
base_model: google/bert_uncased_L-4_H-128_A-2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: bert_uncased_L-4_H-128_A-2-OCR-quality-classification-cls
  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_uncased_L-4_H-128_A-2-OCR-quality-classification-cls

This model is a fine-tuned version of [google/bert_uncased_L-4_H-128_A-2](https://huggingface.co/google/bert_uncased_L-4_H-128_A-2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0422
- Accuracy: 0.99
- Num Input Tokens Seen: 57341952

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 2.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Input Tokens Seen |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-----------------:|
| 0.1123        | 0.2660 | 250  | 0.1202          | 0.974    | 8192000           |
| 0.072         | 0.5321 | 500  | 0.0665          | 0.986    | 16384000          |
| 0.0404        | 0.7981 | 750  | 0.0464          | 0.988    | 24576000          |
| 0.0255        | 1.0641 | 1000 | 0.0428          | 0.99     | 32765952          |
| 0.0253        | 1.3301 | 1250 | 0.0357          | 0.99     | 40957952          |
| 0.0329        | 1.5962 | 1500 | 0.0438          | 0.986    | 49149952          |
| 0.0435        | 1.8622 | 1750 | 0.0422          | 0.99     | 57341952          |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1