| --- |
| license: apache-2.0 |
| base_model: microsoft/resnet-18 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: font-identifier |
| results: |
| - task: |
| name: Image Classification |
| type: image-classification |
| dataset: |
| name: imagefolder |
| type: imagefolder |
| config: default |
| split: test |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.7810232220609579 |
| --- |
| |
| <!-- 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. --> |
|
|
| # font-identifier |
|
|
| This model is a fine-tuned version of [microsoft/resnet-18](https://huggingface.co/microsoft/resnet-18) on the imagefolder dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.8935 |
| - Accuracy: 0.7810 |
|
|
| ## 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: 5e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 64 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 30 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | 7.2836 | 1.0 | 344 | 7.2178 | 0.0038 | |
| | 6.6696 | 2.0 | 689 | 6.4685 | 0.0408 | |
| | 5.85 | 3.0 | 1034 | 5.3897 | 0.1254 | |
| | 5.0457 | 4.0 | 1379 | 4.4771 | 0.2143 | |
| | 4.3784 | 5.0 | 1723 | 3.6429 | 0.3242 | |
| | 3.809 | 6.0 | 2068 | 3.1236 | 0.4031 | |
| | 3.4229 | 7.0 | 2413 | 2.6388 | 0.4672 | |
| | 2.8977 | 8.0 | 2758 | 2.3279 | 0.5102 | |
| | 2.78 | 9.0 | 3102 | 2.0974 | 0.5682 | |
| | 2.4452 | 10.0 | 3447 | 1.8605 | 0.6027 | |
| | 2.2195 | 11.0 | 3792 | 1.6783 | 0.6312 | |
| | 2.1097 | 12.0 | 4137 | 1.6049 | 0.6390 | |
| | 1.9025 | 13.0 | 4481 | 1.4255 | 0.6912 | |
| | 1.7973 | 14.0 | 4826 | 1.3253 | 0.7075 | |
| | 1.7647 | 15.0 | 5171 | 1.3030 | 0.7032 | |
| | 1.6772 | 16.0 | 5516 | 1.1988 | 0.7210 | |
| | 1.5523 | 17.0 | 5860 | 1.1040 | 0.7395 | |
| | 1.4821 | 18.0 | 6205 | 1.0786 | 0.7380 | |
| | 1.3764 | 19.0 | 6550 | 1.0603 | 0.7471 | |
| | 1.2913 | 20.0 | 6895 | 1.0169 | 0.7542 | |
| | 1.3479 | 21.0 | 7239 | 0.9999 | 0.7563 | |
| | 1.3133 | 22.0 | 7584 | 0.9928 | 0.7594 | |
| | 1.2241 | 23.0 | 7929 | 0.9342 | 0.7649 | |
| | 1.1651 | 24.0 | 8274 | 0.9283 | 0.7658 | |
| | 1.1605 | 25.0 | 8618 | 0.9176 | 0.7720 | |
| | 1.0283 | 26.0 | 8963 | 0.8970 | 0.7767 | |
| | 1.1211 | 27.0 | 9308 | 0.8983 | 0.7754 | |
| | 1.1563 | 28.0 | 9653 | 0.8729 | 0.7801 | |
| | 1.1399 | 29.0 | 9997 | 0.9021 | 0.7732 | |
| | 1.1715 | 29.93 | 10320 | 0.8935 | 0.7810 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.35.2 |
| - Pytorch 2.0.0 |
| - Datasets 2.15.0 |
| - Tokenizers 0.15.0 |
|
|
