---
license: mit
base_model: microsoft/xtremedistil-l6-h256-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
datasets:
- pszemraj/OCR-quality-classification
language:
- en
---

# xtremedistil-l6-h256-uncased: OCR-quality-classification

This model is a fine-tuned version of [microsoft/xtremedistil-l6-h256-uncased](https://hf.co/microsoft/xtremedistil-l6-h256-uncased) on `pszemraj/OCR-quality-classification`  

It achieves the following results on the evaluation set:
- Loss: 0.0316
- Accuracy: 0.994
- Num Input Tokens Seen: 57341952

## Intended uses & limitations

predict whether a document is clean or noisy

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-----------------:|
| 0.0812        | 0.2660 | 250  | 0.0860          | 0.986    | 8192000           |
| 0.0637        | 0.5321 | 500  | 0.0532          | 0.988    | 16384000          |
| 0.031         | 0.7981 | 750  | 0.0463          | 0.99     | 24576000          |
| 0.0315        | 1.0641 | 1000 | 0.0343          | 0.992    | 32765952          |
| 0.0223        | 1.3301 | 1250 | 0.0337          | 0.994    | 40957952          |
| 0.0137        | 1.5962 | 1500 | 0.0423          | 0.99     | 49149952          |
| 0.0186        | 1.8622 | 1750 | 0.0316          | 0.994    | 57341952          |


### Framework versions

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