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ariadnak
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font-identifier

Image Classification
Transformers
Safetensors
resnet
Generated from Trainer
Eval Results
Inference Endpoints
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+ ---
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+ license: apache-2.0
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+ base_model: microsoft/resnet-18
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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: font-identifier
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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: default
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+ split: test
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.7810232220609579
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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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+ # font-identifier
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+
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+ This model is a fine-tuned version of [microsoft/resnet-18](https://huggingface.co/microsoft/resnet-18) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8935
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+ - Accuracy: 0.7810
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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: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 64
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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: 30
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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 |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 7.2836 | 1.0 | 344 | 7.2178 | 0.0038 |
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+ | 6.6696 | 2.0 | 689 | 6.4685 | 0.0408 |
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+ | 5.85 | 3.0 | 1034 | 5.3897 | 0.1254 |
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+ | 5.0457 | 4.0 | 1379 | 4.4771 | 0.2143 |
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+ | 4.3784 | 5.0 | 1723 | 3.6429 | 0.3242 |
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+ | 3.809 | 6.0 | 2068 | 3.1236 | 0.4031 |
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+ | 3.4229 | 7.0 | 2413 | 2.6388 | 0.4672 |
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+ | 2.8977 | 8.0 | 2758 | 2.3279 | 0.5102 |
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+ | 2.78 | 9.0 | 3102 | 2.0974 | 0.5682 |
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+ | 2.4452 | 10.0 | 3447 | 1.8605 | 0.6027 |
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+ | 2.2195 | 11.0 | 3792 | 1.6783 | 0.6312 |
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+ | 2.1097 | 12.0 | 4137 | 1.6049 | 0.6390 |
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+ | 1.9025 | 13.0 | 4481 | 1.4255 | 0.6912 |
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+ | 1.7973 | 14.0 | 4826 | 1.3253 | 0.7075 |
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+ | 1.7647 | 15.0 | 5171 | 1.3030 | 0.7032 |
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+ | 1.6772 | 16.0 | 5516 | 1.1988 | 0.7210 |
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+ | 1.5523 | 17.0 | 5860 | 1.1040 | 0.7395 |
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+ | 1.4821 | 18.0 | 6205 | 1.0786 | 0.7380 |
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+ | 1.3764 | 19.0 | 6550 | 1.0603 | 0.7471 |
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+ | 1.2913 | 20.0 | 6895 | 1.0169 | 0.7542 |
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+ | 1.3479 | 21.0 | 7239 | 0.9999 | 0.7563 |
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+ | 1.3133 | 22.0 | 7584 | 0.9928 | 0.7594 |
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+ | 1.2241 | 23.0 | 7929 | 0.9342 | 0.7649 |
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+ | 1.1651 | 24.0 | 8274 | 0.9283 | 0.7658 |
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+ | 1.1605 | 25.0 | 8618 | 0.9176 | 0.7720 |
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+ | 1.0283 | 26.0 | 8963 | 0.8970 | 0.7767 |
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+ | 1.1211 | 27.0 | 9308 | 0.8983 | 0.7754 |
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+ | 1.1563 | 28.0 | 9653 | 0.8729 | 0.7801 |
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+ | 1.1399 | 29.0 | 9997 | 0.9021 | 0.7732 |
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+ | 1.1715 | 29.93 | 10320 | 0.8935 | 0.7810 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.0.0
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+ - Datasets 2.15.0
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+ - Tokenizers 0.15.0