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	---
	license: apache-2.0
	base_model: facebook/dinov2-base
	tags:
	- generated_from_trainer
	metrics:
	- accuracy
	model-index:
	- name: dino-base-2023_10_31-demo-v5
	results: []
	pipeline_tag: image-classification
	---

	<!-- This model card has been generated automatically according to the information the Trainer had access to. You
	should probably proofread and complete it, then remove this comment. -->

	# dino-base-2023_10_31-demo-v5

	This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on the None dataset.
	It achieves the following results on the evaluation set:
	- Loss: 0.0993
	- F1 Micro: 0.8523
	- F1 Macro: 0.7900
	- Roc Auc: 0.9054
	- Accuracy: 0.5712

	## 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: 0.01
	- train_batch_size: 16
	- eval_batch_size: 16
	- seed: 42
	- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
	- lr_scheduler_type: linear
	- num_epochs: 100

	### Training results

	\| Training Loss \| Epoch \| Step \| Validation Loss \| F1 Micro \| F1 Macro \| Roc Auc \| Accuracy \|
	\|:-------------:\|:-----:\|:-----:\|:---------------:\|:--------:\|:--------:\|:-------:\|:--------:\|
	\| 0.1686 \| 1.0 \| 592 \| 0.1334 \| 0.8014 \| 0.7001 \| 0.8691 \| 0.5017 \|
	\| 0.1255 \| 2.0 \| 1184 \| 0.1214 \| 0.8129 \| 0.7228 \| 0.8768 \| 0.5180 \|
	\| 0.1167 \| 3.0 \| 1776 \| 0.1210 \| 0.8167 \| 0.7202 \| 0.8714 \| 0.5259 \|
	\| 0.1087 \| 4.0 \| 2368 \| 0.1209 \| 0.8215 \| 0.7468 \| 0.8967 \| 0.5136 \|
	\| 0.1078 \| 5.0 \| 2960 \| 0.1179 \| 0.8135 \| 0.7248 \| 0.8640 \| 0.5323 \|
	\| 0.0992 \| 6.0 \| 3552 \| 0.1169 \| 0.8280 \| 0.7482 \| 0.9010 \| 0.5224 \|
	\| 0.0961 \| 7.0 \| 4144 \| 0.1144 \| 0.8311 \| 0.7605 \| 0.9004 \| 0.5209 \|
	\| 0.0939 \| 8.0 \| 4736 \| 0.1107 \| 0.8393 \| 0.7503 \| 0.9092 \| 0.5298 \|
	\| 0.0942 \| 9.0 \| 5328 \| 0.1157 \| 0.8249 \| 0.7416 \| 0.8762 \| 0.5515 \|
	\| 0.0922 \| 10.0 \| 5920 \| 0.1072 \| 0.8364 \| 0.7776 \| 0.8973 \| 0.5481 \|
	\| 0.0895 \| 11.0 \| 6512 \| 0.1102 \| 0.8310 \| 0.7631 \| 0.8890 \| 0.5328 \|
	\| 0.0866 \| 12.0 \| 7104 \| 0.1054 \| 0.8473 \| 0.7701 \| 0.9099 \| 0.5451 \|
	\| 0.0872 \| 13.0 \| 7696 \| 0.1055 \| 0.8454 \| 0.7851 \| 0.9097 \| 0.5436 \|
	\| 0.085 \| 14.0 \| 8288 \| 0.1069 \| 0.8422 \| 0.7684 \| 0.9008 \| 0.5559 \|
	\| 0.0854 \| 15.0 \| 8880 \| 0.1106 \| 0.8316 \| 0.7666 \| 0.8926 \| 0.5456 \|
	\| 0.0841 \| 16.0 \| 9472 \| 0.1068 \| 0.8405 \| 0.7681 \| 0.8922 \| 0.5702 \|
	\| 0.0807 \| 17.0 \| 10064 \| 0.1041 \| 0.8460 \| 0.7814 \| 0.9051 \| 0.5594 \|
	\| 0.0819 \| 18.0 \| 10656 \| 0.1053 \| 0.8431 \| 0.7822 \| 0.9046 \| 0.5466 \|
	\| 0.0801 \| 19.0 \| 11248 \| 0.1081 \| 0.8395 \| 0.7683 \| 0.9063 \| 0.5436 \|
	\| 0.0795 \| 20.0 \| 11840 \| 0.1077 \| 0.8451 \| 0.7721 \| 0.8980 \| 0.5520 \|
	\| 0.0798 \| 21.0 \| 12432 \| 0.1069 \| 0.8390 \| 0.7721 \| 0.8839 \| 0.5742 \|
	\| 0.0784 \| 22.0 \| 13024 \| 0.1050 \| 0.8442 \| 0.7847 \| 0.9059 \| 0.5461 \|
	\| 0.0775 \| 23.0 \| 13616 \| 0.1065 \| 0.8443 \| 0.7904 \| 0.9072 \| 0.5476 \|
	\| 0.0727 \| 24.0 \| 14208 \| 0.1010 \| 0.8493 \| 0.7910 \| 0.9051 \| 0.5678 \|
	\| 0.0707 \| 25.0 \| 14800 \| 0.1002 \| 0.8496 \| 0.7877 \| 0.9058 \| 0.5643 \|
	\| 0.0697 \| 26.0 \| 15392 \| 0.1006 \| 0.8489 \| 0.7886 \| 0.9024 \| 0.5692 \|
	\| 0.0699 \| 27.0 \| 15984 \| 0.1005 \| 0.8531 \| 0.7897 \| 0.9054 \| 0.5702 \|
	\| 0.0692 \| 28.0 \| 16576 \| 0.1001 \| 0.8499 \| 0.7894 \| 0.9059 \| 0.5663 \|
	\| 0.0719 \| 29.0 \| 17168 \| 0.0998 \| 0.8524 \| 0.7854 \| 0.9058 \| 0.5737 \|
	\| 0.0686 \| 30.0 \| 17760 \| 0.1006 \| 0.8503 \| 0.7897 \| 0.9033 \| 0.5663 \|
	\| 0.0692 \| 31.0 \| 18352 \| 0.1000 \| 0.8519 \| 0.7928 \| 0.9055 \| 0.5717 \|
	\| 0.0707 \| 32.0 \| 18944 \| 0.1000 \| 0.8517 \| 0.7862 \| 0.9056 \| 0.5737 \|
	\| 0.0695 \| 33.0 \| 19536 \| 0.1002 \| 0.8517 \| 0.7850 \| 0.9012 \| 0.5781 \|
	\| 0.069 \| 34.0 \| 20128 \| 0.1008 \| 0.8477 \| 0.7849 \| 0.9003 \| 0.5658 \|
	\| 0.0686 \| 35.0 \| 20720 \| 0.1004 \| 0.8523 \| 0.7866 \| 0.9009 \| 0.5732 \|
	\| 0.0688 \| 36.0 \| 21312 \| 0.0994 \| 0.8517 \| 0.7902 \| 0.9058 \| 0.5673 \|
	\| 0.0688 \| 37.0 \| 21904 \| 0.0994 \| 0.8523 \| 0.7900 \| 0.9048 \| 0.5732 \|
	\| 0.0677 \| 38.0 \| 22496 \| 0.0994 \| 0.8520 \| 0.7905 \| 0.9051 \| 0.5697 \|
	\| 0.0678 \| 39.0 \| 23088 \| 0.0995 \| 0.8516 \| 0.7911 \| 0.9035 \| 0.5747 \|
	\| 0.068 \| 40.0 \| 23680 \| 0.0994 \| 0.8520 \| 0.7888 \| 0.9039 \| 0.5712 \|
	\| 0.0679 \| 41.0 \| 24272 \| 0.0994 \| 0.8535 \| 0.7908 \| 0.9056 \| 0.5757 \|
	\| 0.0682 \| 42.0 \| 24864 \| 0.0993 \| 0.8517 \| 0.7883 \| 0.9054 \| 0.5707 \|
	\| 0.0677 \| 43.0 \| 25456 \| 0.0994 \| 0.8516 \| 0.7908 \| 0.9052 \| 0.5707 \|
	\| 0.0678 \| 44.0 \| 26048 \| 0.0995 \| 0.8518 \| 0.7916 \| 0.9066 \| 0.5673 \|
	\| 0.0677 \| 45.0 \| 26640 \| 0.0993 \| 0.8519 \| 0.7886 \| 0.9054 \| 0.5702 \|
	\| 0.0684 \| 46.0 \| 27232 \| 0.0995 \| 0.8519 \| 0.7909 \| 0.9060 \| 0.5697 \|
	\| 0.0675 \| 47.0 \| 27824 \| 0.0994 \| 0.8524 \| 0.7908 \| 0.9048 \| 0.5757 \|
	\| 0.067 \| 48.0 \| 28416 \| 0.0995 \| 0.8521 \| 0.7893 \| 0.9044 \| 0.5717 \|
	\| 0.0675 \| 49.0 \| 29008 \| 0.0994 \| 0.8524 \| 0.7902 \| 0.9056 \| 0.5707 \|
	\| 0.0674 \| 50.0 \| 29600 \| 0.0994 \| 0.8517 \| 0.7893 \| 0.9051 \| 0.5692 \|
	\| 0.0679 \| 51.0 \| 30192 \| 0.0993 \| 0.8519 \| 0.7898 \| 0.9052 \| 0.5697 \|
	\| 0.0667 \| 52.0 \| 30784 \| 0.0993 \| 0.8523 \| 0.7900 \| 0.9054 \| 0.5712 \|


	### Framework versions

	- Transformers 4.34.1
	- Pytorch 2.1.0+cu118
	- Datasets 2.14.5
	- Tokenizers 0.14.1

	---
	license: apache-2.0
	base_model: facebook/dinov2-base
	tags:
	- generated_from_trainer
	metrics:
	- accuracy
	model-index:
	- name: dino-base-2023_10_31-demo-v5
	results: []
	pipeline_tag: image-classification
	---

	<!-- This model card has been generated automatically according to the information the Trainer had access to. You
	should probably proofread and complete it, then remove this comment. -->

	# dino-base-2023_10_31-demo-v5

	This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on the None dataset.
	It achieves the following results on the evaluation set:
	- Loss: 0.0993
	- F1 Micro: 0.8523
	- F1 Macro: 0.7900
	- Roc Auc: 0.9054
	- Accuracy: 0.5712

	## 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: 0.01
	- train_batch_size: 16
	- eval_batch_size: 16
	- seed: 42
	- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
	- lr_scheduler_type: linear
	- num_epochs: 100

	### Training results

	\| Training Loss \| Epoch \| Step \| Validation Loss \| F1 Micro \| F1 Macro \| Roc Auc \| Accuracy \|
	\|:-------------:\|:-----:\|:-----:\|:---------------:\|:--------:\|:--------:\|:-------:\|:--------:\|
	\| 0.1686 \| 1.0 \| 592 \| 0.1334 \| 0.8014 \| 0.7001 \| 0.8691 \| 0.5017 \|
	\| 0.1255 \| 2.0 \| 1184 \| 0.1214 \| 0.8129 \| 0.7228 \| 0.8768 \| 0.5180 \|
	\| 0.1167 \| 3.0 \| 1776 \| 0.1210 \| 0.8167 \| 0.7202 \| 0.8714 \| 0.5259 \|
	\| 0.1087 \| 4.0 \| 2368 \| 0.1209 \| 0.8215 \| 0.7468 \| 0.8967 \| 0.5136 \|
	\| 0.1078 \| 5.0 \| 2960 \| 0.1179 \| 0.8135 \| 0.7248 \| 0.8640 \| 0.5323 \|
	\| 0.0992 \| 6.0 \| 3552 \| 0.1169 \| 0.8280 \| 0.7482 \| 0.9010 \| 0.5224 \|
	\| 0.0961 \| 7.0 \| 4144 \| 0.1144 \| 0.8311 \| 0.7605 \| 0.9004 \| 0.5209 \|
	\| 0.0939 \| 8.0 \| 4736 \| 0.1107 \| 0.8393 \| 0.7503 \| 0.9092 \| 0.5298 \|
	\| 0.0942 \| 9.0 \| 5328 \| 0.1157 \| 0.8249 \| 0.7416 \| 0.8762 \| 0.5515 \|
	\| 0.0922 \| 10.0 \| 5920 \| 0.1072 \| 0.8364 \| 0.7776 \| 0.8973 \| 0.5481 \|
	\| 0.0895 \| 11.0 \| 6512 \| 0.1102 \| 0.8310 \| 0.7631 \| 0.8890 \| 0.5328 \|
	\| 0.0866 \| 12.0 \| 7104 \| 0.1054 \| 0.8473 \| 0.7701 \| 0.9099 \| 0.5451 \|
	\| 0.0872 \| 13.0 \| 7696 \| 0.1055 \| 0.8454 \| 0.7851 \| 0.9097 \| 0.5436 \|
	\| 0.085 \| 14.0 \| 8288 \| 0.1069 \| 0.8422 \| 0.7684 \| 0.9008 \| 0.5559 \|
	\| 0.0854 \| 15.0 \| 8880 \| 0.1106 \| 0.8316 \| 0.7666 \| 0.8926 \| 0.5456 \|
	\| 0.0841 \| 16.0 \| 9472 \| 0.1068 \| 0.8405 \| 0.7681 \| 0.8922 \| 0.5702 \|
	\| 0.0807 \| 17.0 \| 10064 \| 0.1041 \| 0.8460 \| 0.7814 \| 0.9051 \| 0.5594 \|
	\| 0.0819 \| 18.0 \| 10656 \| 0.1053 \| 0.8431 \| 0.7822 \| 0.9046 \| 0.5466 \|
	\| 0.0801 \| 19.0 \| 11248 \| 0.1081 \| 0.8395 \| 0.7683 \| 0.9063 \| 0.5436 \|
	\| 0.0795 \| 20.0 \| 11840 \| 0.1077 \| 0.8451 \| 0.7721 \| 0.8980 \| 0.5520 \|
	\| 0.0798 \| 21.0 \| 12432 \| 0.1069 \| 0.8390 \| 0.7721 \| 0.8839 \| 0.5742 \|
	\| 0.0784 \| 22.0 \| 13024 \| 0.1050 \| 0.8442 \| 0.7847 \| 0.9059 \| 0.5461 \|
	\| 0.0775 \| 23.0 \| 13616 \| 0.1065 \| 0.8443 \| 0.7904 \| 0.9072 \| 0.5476 \|
	\| 0.0727 \| 24.0 \| 14208 \| 0.1010 \| 0.8493 \| 0.7910 \| 0.9051 \| 0.5678 \|
	\| 0.0707 \| 25.0 \| 14800 \| 0.1002 \| 0.8496 \| 0.7877 \| 0.9058 \| 0.5643 \|
	\| 0.0697 \| 26.0 \| 15392 \| 0.1006 \| 0.8489 \| 0.7886 \| 0.9024 \| 0.5692 \|
	\| 0.0699 \| 27.0 \| 15984 \| 0.1005 \| 0.8531 \| 0.7897 \| 0.9054 \| 0.5702 \|
	\| 0.0692 \| 28.0 \| 16576 \| 0.1001 \| 0.8499 \| 0.7894 \| 0.9059 \| 0.5663 \|
	\| 0.0719 \| 29.0 \| 17168 \| 0.0998 \| 0.8524 \| 0.7854 \| 0.9058 \| 0.5737 \|
	\| 0.0686 \| 30.0 \| 17760 \| 0.1006 \| 0.8503 \| 0.7897 \| 0.9033 \| 0.5663 \|
	\| 0.0692 \| 31.0 \| 18352 \| 0.1000 \| 0.8519 \| 0.7928 \| 0.9055 \| 0.5717 \|
	\| 0.0707 \| 32.0 \| 18944 \| 0.1000 \| 0.8517 \| 0.7862 \| 0.9056 \| 0.5737 \|
	\| 0.0695 \| 33.0 \| 19536 \| 0.1002 \| 0.8517 \| 0.7850 \| 0.9012 \| 0.5781 \|
	\| 0.069 \| 34.0 \| 20128 \| 0.1008 \| 0.8477 \| 0.7849 \| 0.9003 \| 0.5658 \|
	\| 0.0686 \| 35.0 \| 20720 \| 0.1004 \| 0.8523 \| 0.7866 \| 0.9009 \| 0.5732 \|
	\| 0.0688 \| 36.0 \| 21312 \| 0.0994 \| 0.8517 \| 0.7902 \| 0.9058 \| 0.5673 \|
	\| 0.0688 \| 37.0 \| 21904 \| 0.0994 \| 0.8523 \| 0.7900 \| 0.9048 \| 0.5732 \|
	\| 0.0677 \| 38.0 \| 22496 \| 0.0994 \| 0.8520 \| 0.7905 \| 0.9051 \| 0.5697 \|
	\| 0.0678 \| 39.0 \| 23088 \| 0.0995 \| 0.8516 \| 0.7911 \| 0.9035 \| 0.5747 \|
	\| 0.068 \| 40.0 \| 23680 \| 0.0994 \| 0.8520 \| 0.7888 \| 0.9039 \| 0.5712 \|
	\| 0.0679 \| 41.0 \| 24272 \| 0.0994 \| 0.8535 \| 0.7908 \| 0.9056 \| 0.5757 \|
	\| 0.0682 \| 42.0 \| 24864 \| 0.0993 \| 0.8517 \| 0.7883 \| 0.9054 \| 0.5707 \|
	\| 0.0677 \| 43.0 \| 25456 \| 0.0994 \| 0.8516 \| 0.7908 \| 0.9052 \| 0.5707 \|
	\| 0.0678 \| 44.0 \| 26048 \| 0.0995 \| 0.8518 \| 0.7916 \| 0.9066 \| 0.5673 \|
	\| 0.0677 \| 45.0 \| 26640 \| 0.0993 \| 0.8519 \| 0.7886 \| 0.9054 \| 0.5702 \|
	\| 0.0684 \| 46.0 \| 27232 \| 0.0995 \| 0.8519 \| 0.7909 \| 0.9060 \| 0.5697 \|
	\| 0.0675 \| 47.0 \| 27824 \| 0.0994 \| 0.8524 \| 0.7908 \| 0.9048 \| 0.5757 \|
	\| 0.067 \| 48.0 \| 28416 \| 0.0995 \| 0.8521 \| 0.7893 \| 0.9044 \| 0.5717 \|
	\| 0.0675 \| 49.0 \| 29008 \| 0.0994 \| 0.8524 \| 0.7902 \| 0.9056 \| 0.5707 \|
	\| 0.0674 \| 50.0 \| 29600 \| 0.0994 \| 0.8517 \| 0.7893 \| 0.9051 \| 0.5692 \|
	\| 0.0679 \| 51.0 \| 30192 \| 0.0993 \| 0.8519 \| 0.7898 \| 0.9052 \| 0.5697 \|
	\| 0.0667 \| 52.0 \| 30784 \| 0.0993 \| 0.8523 \| 0.7900 \| 0.9054 \| 0.5712 \|


	### Framework versions

	- Transformers 4.34.1
	- Pytorch 2.1.0+cu118
	- Datasets 2.14.5
	- Tokenizers 0.14.1