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DunnBC22
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dit-base-Business_Documents_Classified_v2

Image Classification
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+ ---
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - imagefolder
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: dit-base-Business_Documents_Classified_v2
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+ results:
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+ - task:
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+ name: Image Classification
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+ type: image-classification
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+ dataset:
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+ name: imagefolder
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+ type: imagefolder
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+ config: data
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+ split: train
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+ args: data
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.826
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+ ---
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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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+
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+ # dit-base-Business_Documents_Classified_v2
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+
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+ This model is a fine-tuned version of [microsoft/dit-base](https://huggingface.co/microsoft/dit-base) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6715
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+ - Accuracy: 0.826
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+ - Weighted f1: 0.8272
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+ - Micro f1: 0.826
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+ - Macro f1: 0.8242
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+ - Weighted recall: 0.826
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+ - Micro recall: 0.826
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+ - Macro recall: 0.8237
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+ - Weighted precision: 0.8327
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+ - Micro precision: 0.826
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+ - Macro precision: 0.8293
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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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
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+ - num_epochs: 18
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 | Micro f1 | Macro f1 | Weighted recall | Micro recall | Macro recall | Weighted precision | Micro precision | Macro precision |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
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+ | 2.7266 | 0.99 | 31 | 2.4738 | 0.208 | 0.1811 | 0.208 | 0.1827 | 0.208 | 0.208 | 0.2101 | 0.2143 | 0.208 | 0.2246 |
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+ | 2.171 | 1.98 | 62 | 1.8510 | 0.423 | 0.3936 | 0.4230 | 0.3925 | 0.423 | 0.423 | 0.4243 | 0.4503 | 0.423 | 0.4446 |
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+ | 1.6525 | 2.98 | 93 | 1.2633 | 0.61 | 0.5884 | 0.61 | 0.5855 | 0.61 | 0.61 | 0.6124 | 0.6377 | 0.61 | 0.6283 |
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+ | 1.346 | 4.0 | 125 | 1.0259 | 0.706 | 0.7023 | 0.706 | 0.6992 | 0.706 | 0.706 | 0.7058 | 0.7095 | 0.706 | 0.7034 |
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+ | 1.253 | 4.99 | 156 | 0.9180 | 0.729 | 0.7277 | 0.729 | 0.7239 | 0.729 | 0.729 | 0.7291 | 0.7340 | 0.729 | 0.7261 |
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+ | 1.0975 | 5.98 | 187 | 0.8859 | 0.747 | 0.7480 | 0.747 | 0.7437 | 0.747 | 0.747 | 0.7472 | 0.7609 | 0.747 | 0.7526 |
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+ | 1.1122 | 6.98 | 218 | 0.8270 | 0.76 | 0.7606 | 0.76 | 0.7578 | 0.76 | 0.76 | 0.7594 | 0.7772 | 0.76 | 0.7727 |
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+ | 1.0365 | 8.0 | 250 | 0.7806 | 0.775 | 0.7759 | 0.775 | 0.7730 | 0.775 | 0.775 | 0.7735 | 0.7957 | 0.775 | 0.7920 |
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+ | 1.004 | 8.99 | 281 | 0.7472 | 0.796 | 0.7977 | 0.796 | 0.7957 | 0.796 | 0.796 | 0.7956 | 0.8193 | 0.796 | 0.8151 |
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+ | 0.9278 | 9.98 | 312 | 0.7296 | 0.795 | 0.7974 | 0.795 | 0.7957 | 0.795 | 0.795 | 0.7953 | 0.8157 | 0.795 | 0.8115 |
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+ | 0.8767 | 10.98 | 343 | 0.7257 | 0.809 | 0.8101 | 0.809 | 0.8078 | 0.809 | 0.809 | 0.8091 | 0.8182 | 0.809 | 0.8136 |
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+ | 0.8656 | 12.0 | 375 | 0.6875 | 0.814 | 0.8137 | 0.8140 | 0.8106 | 0.814 | 0.814 | 0.8122 | 0.8207 | 0.814 | 0.8164 |
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+ | 0.7905 | 12.99 | 406 | 0.7060 | 0.808 | 0.8093 | 0.808 | 0.8071 | 0.808 | 0.808 | 0.8068 | 0.8182 | 0.808 | 0.8145 |
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+ | 0.8804 | 13.98 | 437 | 0.6849 | 0.82 | 0.8214 | 0.82 | 0.8183 | 0.82 | 0.82 | 0.8183 | 0.8260 | 0.82 | 0.8215 |
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+ | 0.8265 | 14.98 | 468 | 0.6821 | 0.816 | 0.8171 | 0.816 | 0.8143 | 0.816 | 0.816 | 0.8142 | 0.8242 | 0.816 | 0.8206 |
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+ | 0.7929 | 16.0 | 500 | 0.6877 | 0.818 | 0.8184 | 0.818 | 0.8152 | 0.818 | 0.818 | 0.8167 | 0.8240 | 0.818 | 0.8186 |
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+ | 0.7993 | 16.99 | 531 | 0.6718 | 0.825 | 0.8259 | 0.825 | 0.8234 | 0.825 | 0.825 | 0.8227 | 0.8306 | 0.825 | 0.8282 |
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+ | 0.7954 | 17.86 | 558 | 0.6715 | 0.826 | 0.8272 | 0.826 | 0.8242 | 0.826 | 0.826 | 0.8237 | 0.8327 | 0.826 | 0.8293 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.28.1
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+ - Pytorch 2.0.0+cu118
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+ - Datasets 2.11.0
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+ - Tokenizers 0.13.3