MAE
This model is a fine-tuned version of 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
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