--- license: apache-2.0 tags: - masked-auto-encoding - generated_from_trainer model-index: - name: MAE results: [] --- # 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