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font-identifier

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font-identifier

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  ---
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- language:
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- - en
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  tags:
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- - font-identification
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- license: mit
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- widget:
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- - text: "What font is this?"
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- - src: https://huggingface.co/gaborcselle/font-identifier/hf_sample/ArchitectsDaughter-Regular_1.png
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- example_title: Architects Daughter
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- - src: https://huggingface.co/gaborcselle/font-identifier/hf_sample/Arial_Bold_39.png
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- example_title: Arial Bold
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- - src: https://huggingface.co/gaborcselle/font-identifier/hf_sample/Courier_28.png
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- example_title: Courier
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- - src: https://huggingface.co/gaborcselle/font-identifier/hf_sample/Helvetica_3.png
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- example_title: Helvetica
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- - src: https://huggingface.co/gaborcselle/font-identifier/hf_sample/IBMPlexSans-Regular_25.png
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- example_title: IBM Plex Sans
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- - src: https://huggingface.co/gaborcselle/font-identifier/hf_sample/Inter-Regular_43.png
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- example_title: Inter
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- - src: https://huggingface.co/gaborcselle/font-identifier/hf_sample/Lobster-Regular_25.png
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- example_title: Lobster
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- - src: https://huggingface.co/gaborcselle/font-identifier/hf_sample/Merriweather-Regular_1.png
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- example_title: Merriweather
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- - src: https://huggingface.co/gaborcselle/font-identifier/hf_sample/Poppins-Regular_22.png
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- example_title: Poppins
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- - src: https://huggingface.co/gaborcselle/font-identifier/hf_sample/RobotoMono-Regular_38.png
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- example_title: Roboto Mono
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- - src: https://huggingface.co/gaborcselle/font-identifier/hf_sample/Times_New_Roman_Bold Italic_26.png
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- example_title: Times New Roman Bold Italic
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- - src: https://huggingface.co/gaborcselle/font-identifier/hf_sample/Times_New_Roman_Italic_16.png
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- example_title: Times New Roman Italic
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- - src: https://huggingface.co/gaborcselle/font-identifier/hf_sample/TitilliumWeb-Regular_5.png
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- example_title: Titillium Web
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- - src: https://huggingface.co/gaborcselle/font-identifier/hf_sample/Trebuchet_MS_Italic_47.png
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- example_title: Trebuchet MS Italic
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- - src: https://huggingface.co/gaborcselle/font-identifier/hf_sample/Trebuchet_MS_11.png
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- example_title: Trebuchet MS
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- - src: https://huggingface.co/gaborcselle/font-identifier/hf_sample/Verdana_Bold_43.png
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- example_title: Verdana Bold
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  ---
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- # Font Identifier Project
 
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- Tinker project, Nov 8, 2023.
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- Follow along:
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- - [On Pebble.social](https://pebble.social/@gabor/111376050835874755)
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- - [On Threads.net](https://www.threads.net/@gaborcselle/post/CzZJpJCpxTz)
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- - [On Twitter](https://twitter.com/gabor/status/1722300841691103467)
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- Generate sample images (note this will work only on Mac): [gen_sample_data.py](gen_sample_data.py)
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- Arrange test images into test and train: [arrange_train_test_images.py](arrange_train_test_images.py)
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- Train a ResNet18 on the data: [train_font_identifier.py](train_font_identifier.py)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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: 0.38979591836734695
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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+ # font-identifier
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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: 2.5735
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+ - Accuracy: 0.3898
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+ ## Model description
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+ More information needed
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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: 3
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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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+ | 3.5314 | 0.98 | 30 | 3.2829 | 0.2082 |
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+ | 2.9107 | 1.98 | 61 | 2.6947 | 0.3633 |
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+ | 2.6604 | 2.93 | 90 | 2.5735 | 0.3898 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.0.dev0
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+ - Pytorch 2.0.0
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+ - Datasets 2.12.0
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+ - Tokenizers 0.14.1