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vit-large-patch32-224-in21k-finetuned-galaxy10-decals

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  1. README.md +39 -41
  2. model.safetensors +1 -1
README.md CHANGED
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  license: apache-2.0
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  base_model: google/vit-large-patch32-224-in21k
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  tags:
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- - image-classification
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- - vision
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  - generated_from_trainer
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  metrics:
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  - accuracy
@@ -20,13 +18,13 @@ should probably proofread and complete it, then remove this comment. -->
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  # vit-large-patch32-224-in21k-finetuned-galaxy10-decals
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- This model is a fine-tuned version of [google/vit-large-patch32-224-in21k](https://huggingface.co/google/vit-large-patch32-224-in21k) on the matthieulel/galaxy10_decals dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5849
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- - Accuracy: 0.8236
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- - Precision: 0.8257
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- - Recall: 0.8236
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- - F1: 0.8212
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  ## Model description
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@@ -46,11 +44,11 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 0.0001
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- - train_batch_size: 32
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- - eval_batch_size: 32
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  - seed: 42
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  - gradient_accumulation_steps: 4
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- - total_train_batch_size: 128
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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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  - lr_scheduler_warmup_ratio: 0.1
@@ -60,36 +58,36 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | 1.1583 | 0.99 | 124 | 1.0551 | 0.7069 | 0.6559 | 0.7069 | 0.6758 |
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- | 0.8599 | 2.0 | 249 | 0.7914 | 0.7621 | 0.7717 | 0.7621 | 0.7557 |
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- | 0.854 | 3.0 | 374 | 0.7115 | 0.7672 | 0.7850 | 0.7672 | 0.7642 |
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- | 0.7282 | 4.0 | 499 | 0.6807 | 0.7683 | 0.7746 | 0.7683 | 0.7604 |
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- | 0.6165 | 4.99 | 623 | 0.6208 | 0.8016 | 0.8088 | 0.8016 | 0.8015 |
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- | 0.5946 | 6.0 | 748 | 0.5850 | 0.8044 | 0.8084 | 0.8044 | 0.8009 |
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- | 0.6243 | 7.0 | 873 | 0.6090 | 0.7931 | 0.8037 | 0.7931 | 0.7935 |
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- | 0.5429 | 8.0 | 998 | 0.5830 | 0.8021 | 0.8087 | 0.8021 | 0.8006 |
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- | 0.558 | 8.99 | 1122 | 0.5725 | 0.8095 | 0.8191 | 0.8095 | 0.8081 |
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- | 0.457 | 10.0 | 1247 | 0.5702 | 0.8123 | 0.8144 | 0.8123 | 0.8085 |
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- | 0.4399 | 11.0 | 1372 | 0.5973 | 0.8021 | 0.8013 | 0.8021 | 0.7995 |
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- | 0.4055 | 12.0 | 1497 | 0.5799 | 0.8157 | 0.8186 | 0.8157 | 0.8122 |
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- | 0.417 | 12.99 | 1621 | 0.6006 | 0.8061 | 0.8175 | 0.8061 | 0.8066 |
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- | 0.3843 | 14.0 | 1746 | 0.5849 | 0.8236 | 0.8257 | 0.8236 | 0.8212 |
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- | 0.371 | 15.0 | 1871 | 0.5711 | 0.8196 | 0.8157 | 0.8196 | 0.8161 |
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- | 0.3546 | 16.0 | 1996 | 0.6050 | 0.8140 | 0.8171 | 0.8140 | 0.8147 |
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- | 0.2935 | 16.99 | 2120 | 0.6425 | 0.8106 | 0.8159 | 0.8106 | 0.8091 |
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- | 0.2505 | 18.0 | 2245 | 0.6569 | 0.8112 | 0.8091 | 0.8112 | 0.8086 |
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- | 0.3094 | 19.0 | 2370 | 0.6558 | 0.8162 | 0.8137 | 0.8162 | 0.8137 |
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- | 0.2739 | 20.0 | 2495 | 0.7201 | 0.8067 | 0.8094 | 0.8067 | 0.8025 |
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- | 0.2224 | 20.99 | 2619 | 0.7227 | 0.8140 | 0.8175 | 0.8140 | 0.8114 |
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- | 0.2359 | 22.0 | 2744 | 0.6941 | 0.8157 | 0.8142 | 0.8157 | 0.8136 |
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- | 0.2535 | 23.0 | 2869 | 0.7086 | 0.8157 | 0.8160 | 0.8157 | 0.8123 |
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- | 0.2047 | 24.0 | 2994 | 0.7185 | 0.8236 | 0.8236 | 0.8236 | 0.8207 |
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- | 0.2162 | 24.99 | 3118 | 0.7135 | 0.8219 | 0.8200 | 0.8219 | 0.8194 |
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- | 0.2297 | 26.0 | 3243 | 0.7269 | 0.8213 | 0.8172 | 0.8213 | 0.8179 |
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- | 0.2048 | 27.0 | 3368 | 0.7392 | 0.8145 | 0.8156 | 0.8145 | 0.8143 |
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- | 0.2156 | 28.0 | 3493 | 0.7453 | 0.8207 | 0.8182 | 0.8207 | 0.8174 |
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- | 0.1785 | 28.99 | 3617 | 0.7497 | 0.8168 | 0.8157 | 0.8168 | 0.8145 |
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- | 0.1785 | 29.82 | 3720 | 0.7429 | 0.8202 | 0.8190 | 0.8202 | 0.8173 |
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  ### Framework versions
 
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  license: apache-2.0
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  base_model: google/vit-large-patch32-224-in21k
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  tags:
 
 
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  - generated_from_trainer
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  metrics:
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  - accuracy
 
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  # vit-large-patch32-224-in21k-finetuned-galaxy10-decals
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+ This model is a fine-tuned version of [google/vit-large-patch32-224-in21k](https://huggingface.co/google/vit-large-patch32-224-in21k) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5907
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+ - Accuracy: 0.8360
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+ - Precision: 0.8348
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+ - Recall: 0.8360
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+ - F1: 0.8345
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 0.0001
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+ - train_batch_size: 128
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+ - eval_batch_size: 128
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  - seed: 42
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  - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 512
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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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  - lr_scheduler_warmup_ratio: 0.1
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 1.8923 | 0.99 | 31 | 1.6725 | 0.4600 | 0.5537 | 0.4600 | 0.3682 |
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+ | 1.1787 | 1.98 | 62 | 0.9949 | 0.7339 | 0.7513 | 0.7339 | 0.7095 |
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+ | 0.9165 | 2.98 | 93 | 0.7946 | 0.7700 | 0.7694 | 0.7700 | 0.7540 |
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+ | 0.802 | 4.0 | 125 | 0.6747 | 0.7948 | 0.7954 | 0.7948 | 0.7843 |
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+ | 0.7074 | 4.99 | 156 | 0.6196 | 0.8117 | 0.8139 | 0.8117 | 0.8115 |
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+ | 0.6424 | 5.98 | 187 | 0.6205 | 0.8021 | 0.8075 | 0.8021 | 0.7961 |
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+ | 0.6309 | 6.98 | 218 | 0.5760 | 0.8117 | 0.8231 | 0.8117 | 0.8127 |
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+ | 0.5682 | 8.0 | 250 | 0.5748 | 0.8151 | 0.8196 | 0.8151 | 0.8157 |
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+ | 0.5981 | 8.99 | 281 | 0.5704 | 0.8213 | 0.8269 | 0.8213 | 0.8158 |
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+ | 0.547 | 9.98 | 312 | 0.5282 | 0.8377 | 0.8352 | 0.8377 | 0.8345 |
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+ | 0.5067 | 10.98 | 343 | 0.5281 | 0.8382 | 0.8372 | 0.8382 | 0.8356 |
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+ | 0.5066 | 12.0 | 375 | 0.5441 | 0.8247 | 0.8286 | 0.8247 | 0.8219 |
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+ | 0.4919 | 12.99 | 406 | 0.5580 | 0.8157 | 0.8236 | 0.8157 | 0.8155 |
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+ | 0.4508 | 13.98 | 437 | 0.5269 | 0.8303 | 0.8331 | 0.8303 | 0.8279 |
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+ | 0.4415 | 14.98 | 468 | 0.5399 | 0.8185 | 0.8249 | 0.8185 | 0.8203 |
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+ | 0.4178 | 16.0 | 500 | 0.5229 | 0.8320 | 0.8358 | 0.8320 | 0.8301 |
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+ | 0.366 | 16.99 | 531 | 0.5427 | 0.8275 | 0.8281 | 0.8275 | 0.8241 |
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+ | 0.3706 | 17.98 | 562 | 0.5389 | 0.8241 | 0.8242 | 0.8241 | 0.8230 |
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+ | 0.3609 | 18.98 | 593 | 0.5573 | 0.8247 | 0.8262 | 0.8247 | 0.8239 |
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+ | 0.3443 | 20.0 | 625 | 0.5605 | 0.8320 | 0.8325 | 0.8320 | 0.8302 |
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+ | 0.3214 | 20.99 | 656 | 0.5667 | 0.8281 | 0.8295 | 0.8281 | 0.8254 |
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+ | 0.3262 | 21.98 | 687 | 0.5797 | 0.8236 | 0.8237 | 0.8236 | 0.8214 |
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+ | 0.299 | 22.98 | 718 | 0.5938 | 0.8202 | 0.8225 | 0.8202 | 0.8195 |
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+ | 0.2792 | 24.0 | 750 | 0.5909 | 0.8275 | 0.8258 | 0.8275 | 0.8251 |
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+ | 0.2969 | 24.99 | 781 | 0.5658 | 0.8309 | 0.8319 | 0.8309 | 0.8306 |
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+ | 0.2559 | 25.98 | 812 | 0.5936 | 0.8309 | 0.8294 | 0.8309 | 0.8294 |
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+ | 0.2756 | 26.98 | 843 | 0.5898 | 0.8292 | 0.8295 | 0.8292 | 0.8287 |
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+ | 0.254 | 28.0 | 875 | 0.6043 | 0.8303 | 0.8319 | 0.8303 | 0.8289 |
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+ | 0.2674 | 28.99 | 906 | 0.5950 | 0.8371 | 0.8365 | 0.8371 | 0.8353 |
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+ | 0.2432 | 29.76 | 930 | 0.5907 | 0.8360 | 0.8348 | 0.8360 | 0.8345 |
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  ### Framework versions
model.safetensors CHANGED
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