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--- |
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license: mit |
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base_model: |
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- magistermilitum/tridis_HTR |
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library_name: transformers |
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language: |
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- la |
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tags: |
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- trOCR |
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- HTR |
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- text_recognition |
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- history |
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- latin |
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--- |
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<h1>Textrecognition Model for Essoins (England) in Latin</h1> |
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Part of the developments within the [Flow-Project](https://www.flow-project.net/). |
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Developed by Jonas Widmer, Christopher Kuhlmann, and Melvin Wilde. |
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Base model: **magistermilitum/tridis_HTR v1** |
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Train Lines: 15356 |
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Eval Lines: 394 |
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Test Lines: 2995 |
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Epochs: 14.1667 / 20 |
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Eval CER: 0.0544 |
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Test CER: 0.0622 |
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Testresults with CERberus |
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| Metric | Value | |
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|----------------------------|---------| |
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| Character Error Rate | 6.22 | |
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| Number of Correct Characters| 186998 | |
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| Number of Substitutions | 5425 | |
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| Number of Insertions | 2933 | |
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| Number of Deletions | 3849 | |
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| Total Character Count | 196272 | |
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| Original Lines Count | 2288 | |
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| Discarded Lines Count | 0 | |
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| Block | Count | Correct | Incorrect | Correct Ratio | Incorrect Ratio | |
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|------------------------------|---------|-----------|-------------|-----------------|-------------------| |
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| Digits | 0 | 0 | 0 | nan | nan | |
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| Lowercase Latin alphabet | 154731 | 147241 | 7490 | 95.16 | 4.84 | |
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| MUFI Glyphs | 0 | 0 | 0 | nan | nan | |
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| Punctuation | 9 | 4 | 5 | 44.44 | 55.56 | |
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| Uppercase Latin alphabet | 6883 | 6450 | 433 | 93.71 | 6.29 | |
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The handwritten texts in Latin (with some Middle-English and Anglo-Norman wording) that were used for training are from the 13th and 14th centuries. They come from England and were written in 'Court Hand', also known as 'Anglicana'. They come from the 'Court of Common Pleas', the second highest court of the time, and deal primarily with civil disputes, such as inheritances or dowries, and from the Justices, which also dealt with civil pleas, but covered crown pleas as well. |
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The model has not been extensively tested. |
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Errors often occur in the Punctuation, which itself has an error rate of 44.44% which mostly consits of missed ‧ dots. |
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Potential biases are still to be identified. |
