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kevinoli
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clip-finetuned-csu-p14-336-e4l58-l

Zero-Shot Image Classification
Transformers
TensorBoard
Safetensors
clip
Generated from Trainer
Inference Endpoints
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  1. README.md +76 -44
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@@ -15,7 +15,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [openai/clip-vit-large-patch14-336](https://huggingface.co/openai/clip-vit-large-patch14-336) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8656
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  ## Model description
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@@ -46,49 +46,81 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:------:|:-----:|:---------------:|
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- | 0.3758 | 0.0921 | 500 | 1.4185 |
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- | 0.4103 | 0.1842 | 1000 | 1.3501 |
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- | 0.433 | 0.2763 | 1500 | 1.2885 |
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- | 0.3424 | 0.3685 | 2000 | 1.2391 |
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- | 0.3645 | 0.4606 | 2500 | 1.1902 |
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- | 0.3172 | 0.5527 | 3000 | 1.1506 |
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- | 0.2751 | 0.6448 | 3500 | 1.1169 |
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- | 0.2919 | 0.7369 | 4000 | 1.0921 |
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- | 0.2583 | 0.8290 | 4500 | 1.0721 |
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- | 0.2679 | 0.9211 | 5000 | 1.0519 |
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- | 0.2472 | 1.0133 | 5500 | 1.0356 |
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- | 0.26 | 1.1054 | 6000 | 1.0177 |
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- | 0.2153 | 1.1975 | 6500 | 1.0045 |
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- | 0.1791 | 1.2896 | 7000 | 0.9927 |
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- | 0.2082 | 1.3817 | 7500 | 0.9804 |
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- | 0.196 | 1.4738 | 8000 | 0.9712 |
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- | 0.1946 | 1.5660 | 8500 | 0.9621 |
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- | 0.2422 | 1.6581 | 9000 | 0.9537 |
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- | 0.2106 | 1.7502 | 9500 | 0.9458 |
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- | 0.1801 | 1.8423 | 10000 | 0.9393 |
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- | 0.2117 | 1.9344 | 10500 | 0.9308 |
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- | 0.2061 | 2.0265 | 11000 | 0.9237 |
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- | 0.1878 | 2.1186 | 11500 | 0.9167 |
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- | 0.1655 | 2.2108 | 12000 | 0.9109 |
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- | 0.1946 | 2.3029 | 12500 | 0.9071 |
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- | 0.1882 | 2.3950 | 13000 | 0.9021 |
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- | 0.1871 | 2.4871 | 13500 | 0.8960 |
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- | 0.1419 | 2.5792 | 14000 | 0.8913 |
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- | 0.1431 | 2.6713 | 14500 | 0.8879 |
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- | 0.1811 | 2.7634 | 15000 | 0.8848 |
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- | 0.1694 | 2.8556 | 15500 | 0.8827 |
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- | 0.1718 | 2.9477 | 16000 | 0.8798 |
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- | 0.153 | 3.0398 | 16500 | 0.8777 |
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- | 0.1715 | 3.1319 | 17000 | 0.8759 |
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- | 0.1558 | 3.2240 | 17500 | 0.8742 |
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- | 0.1384 | 3.3161 | 18000 | 0.8715 |
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- | 0.1788 | 3.4083 | 18500 | 0.8695 |
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- | 0.1668 | 3.5004 | 19000 | 0.8685 |
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- | 0.1697 | 3.5925 | 19500 | 0.8674 |
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- | 0.1764 | 3.6846 | 20000 | 0.8666 |
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- | 0.1417 | 3.7767 | 20500 | 0.8660 |
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- | 0.1556 | 3.8688 | 21000 | 0.8657 |
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- | 0.1605 | 3.9609 | 21500 | 0.8656 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [openai/clip-vit-large-patch14-336](https://huggingface.co/openai/clip-vit-large-patch14-336) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.8028
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:------:|:-----:|:---------------:|
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+ | 0.4667 | 0.0533 | 500 | 1.4426 |
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+ | 0.4532 | 0.1067 | 1000 | 1.3816 |
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+ | 0.3749 | 0.1600 | 1500 | 1.3311 |
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+ | 0.336 | 0.2133 | 2000 | 1.2891 |
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+ | 0.3585 | 0.2666 | 2500 | 1.2536 |
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+ | 0.303 | 0.3200 | 3000 | 1.2203 |
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+ | 0.3242 | 0.3733 | 3500 | 1.1956 |
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+ | 0.2427 | 0.4266 | 4000 | 1.1694 |
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+ | 0.2993 | 0.4799 | 4500 | 1.1456 |
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+ | 0.3183 | 0.5333 | 5000 | 1.1201 |
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+ | 0.307 | 0.5866 | 5500 | 1.0982 |
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+ | 0.2638 | 0.6399 | 6000 | 1.0780 |
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+ | 0.2226 | 0.6933 | 6500 | 1.0613 |
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+ | 0.2453 | 0.7466 | 7000 | 1.0444 |
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+ | 0.272 | 0.7999 | 7500 | 1.0301 |
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+ | 0.283 | 0.8532 | 8000 | 1.0167 |
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+ | 0.2331 | 0.9066 | 8500 | 1.0035 |
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+ | 0.2362 | 0.9599 | 9000 | 0.9925 |
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+ | 0.2396 | 1.0132 | 9500 | 0.9830 |
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+ | 0.2013 | 1.0666 | 10000 | 0.9736 |
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+ | 0.2082 | 1.1199 | 10500 | 0.9639 |
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+ | 0.2023 | 1.1732 | 11000 | 0.9558 |
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+ | 0.2331 | 1.2265 | 11500 | 0.9465 |
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+ | 0.1784 | 1.2799 | 12000 | 0.9392 |
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+ | 0.1953 | 1.3332 | 12500 | 0.9316 |
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+ | 0.1867 | 1.3865 | 13000 | 0.9270 |
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+ | 0.22 | 1.4398 | 13500 | 0.9197 |
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+ | 0.1656 | 1.4932 | 14000 | 0.9148 |
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+ | 0.1968 | 1.5465 | 14500 | 0.9096 |
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+ | 0.1676 | 1.5998 | 15000 | 0.9057 |
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+ | 0.2074 | 1.6532 | 15500 | 0.8994 |
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+ | 0.1847 | 1.7065 | 16000 | 0.8954 |
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+ | 0.1845 | 1.7598 | 16500 | 0.8900 |
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+ | 0.1721 | 1.8131 | 17000 | 0.8873 |
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+ | 0.2627 | 1.8665 | 17500 | 0.8810 |
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+ | 0.1623 | 1.9198 | 18000 | 0.8774 |
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+ | 0.2162 | 1.9731 | 18500 | 0.8713 |
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+ | 0.1802 | 2.0265 | 19000 | 0.8679 |
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+ | 0.179 | 2.0798 | 19500 | 0.8633 |
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+ | 0.1549 | 2.1331 | 20000 | 0.8606 |
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+ | 0.1742 | 2.1864 | 20500 | 0.8585 |
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+ | 0.1448 | 2.2398 | 21000 | 0.8546 |
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+ | 0.2066 | 2.2931 | 21500 | 0.8513 |
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+ | 0.1483 | 2.3464 | 22000 | 0.8481 |
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+ | 0.1813 | 2.3997 | 22500 | 0.8447 |
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+ | 0.1617 | 2.4531 | 23000 | 0.8411 |
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+ | 0.1664 | 2.5064 | 23500 | 0.8394 |
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+ | 0.1786 | 2.5597 | 24000 | 0.8358 |
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+ | 0.1465 | 2.6131 | 24500 | 0.8330 |
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+ | 0.1289 | 2.6664 | 25000 | 0.8314 |
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+ | 0.1662 | 2.7197 | 25500 | 0.8296 |
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+ | 0.1463 | 2.7730 | 26000 | 0.8262 |
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+ | 0.1471 | 2.8264 | 26500 | 0.8249 |
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+ | 0.167 | 2.8797 | 27000 | 0.8219 |
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+ | 0.1268 | 2.9330 | 27500 | 0.8204 |
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+ | 0.177 | 2.9863 | 28000 | 0.8177 |
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+ | 0.1206 | 3.0397 | 28500 | 0.8166 |
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+ | 0.1345 | 3.0930 | 29000 | 0.8156 |
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+ | 0.1907 | 3.1463 | 29500 | 0.8144 |
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+ | 0.1395 | 3.1997 | 30000 | 0.8126 |
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+ | 0.1511 | 3.2530 | 30500 | 0.8112 |
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+ | 0.1334 | 3.3063 | 31000 | 0.8102 |
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+ | 0.1799 | 3.3596 | 31500 | 0.8090 |
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+ | 0.1289 | 3.4130 | 32000 | 0.8081 |
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+ | 0.1545 | 3.4663 | 32500 | 0.8072 |
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+ | 0.1705 | 3.5196 | 33000 | 0.8064 |
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+ | 0.1424 | 3.5730 | 33500 | 0.8055 |
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+ | 0.1873 | 3.6263 | 34000 | 0.8048 |
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+ | 0.1432 | 3.6796 | 34500 | 0.8043 |
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+ | 0.1485 | 3.7329 | 35000 | 0.8037 |
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+ | 0.1286 | 3.7863 | 35500 | 0.8033 |
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+ | 0.1469 | 3.8396 | 36000 | 0.8030 |
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+ | 0.1708 | 3.8929 | 36500 | 0.8029 |
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+ | 0.1226 | 3.9462 | 37000 | 0.8028 |
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+ | 0.1549 | 3.9996 | 37500 | 0.8028 |
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  ### Framework versions