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license: apache-2.0 |
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tags: |
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- masked-image-modeling |
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- generated_from_trainer |
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model-index: |
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- name: samolet_encoder_finetuned |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# samolet_encoder_finetuned |
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the ummagumm-a/samolet_frames dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1165 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 1337 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 30.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.3356 | 1.0 | 87 | 0.3257 | |
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| 0.2405 | 2.0 | 174 | 0.2403 | |
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| 0.1623 | 3.0 | 261 | 0.1606 | |
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| 0.1452 | 4.0 | 348 | 0.1454 | |
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| 0.1373 | 5.0 | 435 | 0.1413 | |
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| 0.1304 | 6.0 | 522 | 0.1369 | |
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| 0.129 | 7.0 | 609 | 0.1346 | |
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| 0.1291 | 8.0 | 696 | 0.1299 | |
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| 0.1277 | 9.0 | 783 | 0.1294 | |
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| 0.1244 | 10.0 | 870 | 0.1284 | |
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| 0.1275 | 11.0 | 957 | 0.1285 | |
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| 0.1196 | 12.0 | 1044 | 0.1264 | |
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| 0.1219 | 13.0 | 1131 | 0.1263 | |
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| 0.1195 | 14.0 | 1218 | 0.1265 | |
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| 0.1231 | 15.0 | 1305 | 0.1239 | |
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| 0.1208 | 16.0 | 1392 | 0.1216 | |
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| 0.118 | 17.0 | 1479 | 0.1223 | |
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| 0.1143 | 18.0 | 1566 | 0.1201 | |
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| 0.1177 | 19.0 | 1653 | 0.1198 | |
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| 0.1139 | 20.0 | 1740 | 0.1194 | |
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| 0.1152 | 21.0 | 1827 | 0.1193 | |
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| 0.1162 | 22.0 | 1914 | 0.1199 | |
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| 0.1113 | 23.0 | 2001 | 0.1183 | |
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| 0.1134 | 24.0 | 2088 | 0.1183 | |
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| 0.1136 | 25.0 | 2175 | 0.1184 | |
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| 0.1132 | 26.0 | 2262 | 0.1196 | |
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| 0.1156 | 27.0 | 2349 | 0.1185 | |
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| 0.1153 | 28.0 | 2436 | 0.1166 | |
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| 0.1139 | 29.0 | 2523 | 0.1153 | |
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| 0.1103 | 30.0 | 2610 | 0.1164 | |
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### Framework versions |
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- Transformers 4.30.0.dev0 |
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- Pytorch 2.0.1 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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