readme: fix link reference for ByT5 embedding implementation
Browse files
README.md
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@@ -27,7 +27,7 @@ The following NEs were annotated: `PER`, `LOC` and `ORG`.
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# ⚠️ Inference Widget ⚠️
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Fine-Tuning ByT5 models in Flair is currently done by implementing an own [`ByT5Embedding`][
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This class needs to be present when running the model with Flair.
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@@ -35,7 +35,7 @@ Thus, the inference widget is not working with hmByT5 at the moment on the Model
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This should be fixed in future, when ByT5 fine-tuning is supported in Flair directly.
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[
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# Results
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@@ -53,28 +53,28 @@ And report micro F1-score on development set:
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| bs4-e10-lr0.00016 | [0.8516][11] | [0.8654][12] | [0.87][13] | [0.8642][14] | [0.8541][15] | 86.11 ± 0.7 |
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| bs4-e10-lr0.00015 | [0.8599][16] | [0.8649][17] | [0.8652][18] | [0.8482][19] | [0.854][20] | 85.84 ± 0.65 |
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[1]: https://hf.co/
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[2]: https://hf.co/
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[3]: https://hf.co/
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[4]: https://hf.co/
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[5]: https://hf.co/
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[6]: https://hf.co/
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[7]: https://hf.co/
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[8]: https://hf.co/
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[9]: https://hf.co/
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[10]: https://hf.co/
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[11]: https://hf.co/
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[12]: https://hf.co/
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[13]: https://hf.co/
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[14]: https://hf.co/
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[15]: https://hf.co/
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[16]: https://hf.co/
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[17]: https://hf.co/
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[18]: https://hf.co/
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[19]: https://hf.co/
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[20]: https://hf.co/
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The [training log](training.log) and TensorBoard logs are also uploaded to the model hub.
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More information about fine-tuning can be found [here](https://github.com/stefan-it/hmBench).
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# ⚠️ Inference Widget ⚠️
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Fine-Tuning ByT5 models in Flair is currently done by implementing an own [`ByT5Embedding`][0] class.
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This class needs to be present when running the model with Flair.
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This should be fixed in future, when ByT5 fine-tuning is supported in Flair directly.
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[0]: https://github.com/stefan-it/hmBench/blob/main/byt5_embeddings.py
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# Results
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| bs4-e10-lr0.00016 | [0.8516][11] | [0.8654][12] | [0.87][13] | [0.8642][14] | [0.8541][15] | 86.11 ± 0.7 |
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| bs4-e10-lr0.00015 | [0.8599][16] | [0.8649][17] | [0.8652][18] | [0.8482][19] | [0.854][20] | 85.84 ± 0.65 |
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[1]: https://hf.co/stefan-it/hmbench-icdar-nl-hmbyt5-bs8-wsFalse-e10-lr0.00015-poolingfirst-layers-1-crfFalse-1
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[2]: https://hf.co/stefan-it/hmbench-icdar-nl-hmbyt5-bs8-wsFalse-e10-lr0.00015-poolingfirst-layers-1-crfFalse-2
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[3]: https://hf.co/stefan-it/hmbench-icdar-nl-hmbyt5-bs8-wsFalse-e10-lr0.00015-poolingfirst-layers-1-crfFalse-3
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[4]: https://hf.co/stefan-it/hmbench-icdar-nl-hmbyt5-bs8-wsFalse-e10-lr0.00015-poolingfirst-layers-1-crfFalse-4
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[5]: https://hf.co/stefan-it/hmbench-icdar-nl-hmbyt5-bs8-wsFalse-e10-lr0.00015-poolingfirst-layers-1-crfFalse-5
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[6]: https://hf.co/stefan-it/hmbench-icdar-nl-hmbyt5-bs8-wsFalse-e10-lr0.00016-poolingfirst-layers-1-crfFalse-1
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[7]: https://hf.co/stefan-it/hmbench-icdar-nl-hmbyt5-bs8-wsFalse-e10-lr0.00016-poolingfirst-layers-1-crfFalse-2
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[8]: https://hf.co/stefan-it/hmbench-icdar-nl-hmbyt5-bs8-wsFalse-e10-lr0.00016-poolingfirst-layers-1-crfFalse-3
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[9]: https://hf.co/stefan-it/hmbench-icdar-nl-hmbyt5-bs8-wsFalse-e10-lr0.00016-poolingfirst-layers-1-crfFalse-4
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[10]: https://hf.co/stefan-it/hmbench-icdar-nl-hmbyt5-bs8-wsFalse-e10-lr0.00016-poolingfirst-layers-1-crfFalse-5
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[11]: https://hf.co/stefan-it/hmbench-icdar-nl-hmbyt5-bs4-wsFalse-e10-lr0.00016-poolingfirst-layers-1-crfFalse-1
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[12]: https://hf.co/stefan-it/hmbench-icdar-nl-hmbyt5-bs4-wsFalse-e10-lr0.00016-poolingfirst-layers-1-crfFalse-2
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[13]: https://hf.co/stefan-it/hmbench-icdar-nl-hmbyt5-bs4-wsFalse-e10-lr0.00016-poolingfirst-layers-1-crfFalse-3
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[14]: https://hf.co/stefan-it/hmbench-icdar-nl-hmbyt5-bs4-wsFalse-e10-lr0.00016-poolingfirst-layers-1-crfFalse-4
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[15]: https://hf.co/stefan-it/hmbench-icdar-nl-hmbyt5-bs4-wsFalse-e10-lr0.00016-poolingfirst-layers-1-crfFalse-5
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[16]: https://hf.co/stefan-it/hmbench-icdar-nl-hmbyt5-bs4-wsFalse-e10-lr0.00015-poolingfirst-layers-1-crfFalse-1
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[17]: https://hf.co/stefan-it/hmbench-icdar-nl-hmbyt5-bs4-wsFalse-e10-lr0.00015-poolingfirst-layers-1-crfFalse-2
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[18]: https://hf.co/stefan-it/hmbench-icdar-nl-hmbyt5-bs4-wsFalse-e10-lr0.00015-poolingfirst-layers-1-crfFalse-3
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[19]: https://hf.co/stefan-it/hmbench-icdar-nl-hmbyt5-bs4-wsFalse-e10-lr0.00015-poolingfirst-layers-1-crfFalse-4
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[20]: https://hf.co/stefan-it/hmbench-icdar-nl-hmbyt5-bs4-wsFalse-e10-lr0.00015-poolingfirst-layers-1-crfFalse-5
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The [training log](training.log) and TensorBoard logs (only for hmByT5 and hmTEAMS based models) are also uploaded to the model hub.
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More information about fine-tuning can be found [here](https://github.com/stefan-it/hmBench).
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