---
license: apache-2.0
tags:
- masked-auto-encoding
- generated_from_trainer
model-index:
- name: MAE
  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. -->

# MAE

This model is a fine-tuned version of [facebook/vit-mae-base](https://huggingface.co/facebook/vit-mae-base) on the Circularmachines/batch_indexing_machine_224x224_images dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2263

## 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: 4.6875e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.249         | 1.0   | 7705  | 0.2445          |
| 0.2269        | 2.0   | 15410 | 0.2373          |
| 0.2401        | 3.0   | 23115 | 0.2334          |
| 0.2202        | 4.0   | 30820 | 0.2305          |
| 0.2173        | 5.0   | 38525 | 0.2283          |
| 0.2347        | 6.0   | 46230 | 0.2282          |
| 0.2304        | 7.0   | 53935 | 0.2268          |
| 0.2267        | 8.0   | 61640 | 0.2262          |
| 0.2177        | 9.0   | 69345 | 0.2254          |
| 0.2175        | 10.0  | 77050 | 0.2262          |


### Framework versions

- Transformers 4.29.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3