Upload README.md with huggingface_hub (#1)
Browse files- Upload README.md with huggingface_hub (7eb09aa265f44a4afb677ce01d2c086121bc9bbc)
README.md
ADDED
@@ -0,0 +1,74 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
language: de
|
3 |
+
license: mit
|
4 |
+
tags:
|
5 |
+
- flair
|
6 |
+
- token-classification
|
7 |
+
- sequence-tagger-model
|
8 |
+
base_model: hmbyt5-preliminary/byt5-small-historic-multilingual-span20-flax
|
9 |
+
widget:
|
10 |
+
- text: — Dramatiſch war der Stoff vor Sophokles von Äſchylos behandelt worden in
|
11 |
+
den Θροῇσσαι , denen vielleicht in der Trilogie das Stüc>"OnJw» κοίσις vorherging
|
12 |
+
, das Stück Σαλαμίνιαι folgte .
|
13 |
+
---
|
14 |
+
|
15 |
+
# Fine-tuned Flair Model on AjMC German NER Dataset (HIPE-2022)
|
16 |
+
|
17 |
+
This Flair model was fine-tuned on the
|
18 |
+
[AjMC German](https://github.com/hipe-eval/HIPE-2022-data/blob/main/documentation/README-ajmc.md)
|
19 |
+
NER Dataset using hmByT5 as backbone LM.
|
20 |
+
|
21 |
+
The AjMC dataset consists of NE-annotated historical commentaries in the field of Classics,
|
22 |
+
and was created in the context of the [Ajax MultiCommentary](https://mromanello.github.io/ajax-multi-commentary/)
|
23 |
+
project.
|
24 |
+
|
25 |
+
The following NEs were annotated: `pers`, `work`, `loc`, `object`, `date` and `scope`.
|
26 |
+
|
27 |
+
# Results
|
28 |
+
|
29 |
+
We performed a hyper-parameter search over the following parameters with 5 different seeds per configuration:
|
30 |
+
|
31 |
+
* Batch Sizes: `[8, 4]`
|
32 |
+
* Learning Rates: `[0.00015, 0.00016]`
|
33 |
+
|
34 |
+
And report micro F1-score on development set:
|
35 |
+
|
36 |
+
| Configuration | Run 1 | Run 2 | Run 3 | Run 4 | Run 5 | Avg. |
|
37 |
+
|-------------------|--------------|--------------|--------------|--------------|--------------|--------------|
|
38 |
+
| bs4-e10-lr0.00016 | [0.8892][1] | [0.8913][2] | [0.8867][3] | [0.8843][4] | [0.8828][5] | 88.69 ± 0.31 |
|
39 |
+
| bs4-e10-lr0.00015 | [0.8786][6] | [0.8793][7] | [0.883][8] | [0.8807][9] | [0.8722][10] | 87.88 ± 0.36 |
|
40 |
+
| bs8-e10-lr0.00016 | [0.8602][11] | [0.8684][12] | [0.8643][13] | [0.8643][14] | [0.8623][15] | 86.39 ± 0.27 |
|
41 |
+
| bs8-e10-lr0.00015 | [0.8551][16] | [0.8707][17] | [0.8599][18] | [0.8609][19] | [0.8612][20] | 86.16 ± 0.51 |
|
42 |
+
|
43 |
+
[1]: https://hf.co/hmbench/hmbench-ajmc-de-hmbyt5-bs4-wsFalse-e10-lr0.00016-poolingfirst-layers-1-crfFalse-1
|
44 |
+
[2]: https://hf.co/hmbench/hmbench-ajmc-de-hmbyt5-bs4-wsFalse-e10-lr0.00016-poolingfirst-layers-1-crfFalse-2
|
45 |
+
[3]: https://hf.co/hmbench/hmbench-ajmc-de-hmbyt5-bs4-wsFalse-e10-lr0.00016-poolingfirst-layers-1-crfFalse-3
|
46 |
+
[4]: https://hf.co/hmbench/hmbench-ajmc-de-hmbyt5-bs4-wsFalse-e10-lr0.00016-poolingfirst-layers-1-crfFalse-4
|
47 |
+
[5]: https://hf.co/hmbench/hmbench-ajmc-de-hmbyt5-bs4-wsFalse-e10-lr0.00016-poolingfirst-layers-1-crfFalse-5
|
48 |
+
[6]: https://hf.co/hmbench/hmbench-ajmc-de-hmbyt5-bs4-wsFalse-e10-lr0.00015-poolingfirst-layers-1-crfFalse-1
|
49 |
+
[7]: https://hf.co/hmbench/hmbench-ajmc-de-hmbyt5-bs4-wsFalse-e10-lr0.00015-poolingfirst-layers-1-crfFalse-2
|
50 |
+
[8]: https://hf.co/hmbench/hmbench-ajmc-de-hmbyt5-bs4-wsFalse-e10-lr0.00015-poolingfirst-layers-1-crfFalse-3
|
51 |
+
[9]: https://hf.co/hmbench/hmbench-ajmc-de-hmbyt5-bs4-wsFalse-e10-lr0.00015-poolingfirst-layers-1-crfFalse-4
|
52 |
+
[10]: https://hf.co/hmbench/hmbench-ajmc-de-hmbyt5-bs4-wsFalse-e10-lr0.00015-poolingfirst-layers-1-crfFalse-5
|
53 |
+
[11]: https://hf.co/hmbench/hmbench-ajmc-de-hmbyt5-bs8-wsFalse-e10-lr0.00016-poolingfirst-layers-1-crfFalse-1
|
54 |
+
[12]: https://hf.co/hmbench/hmbench-ajmc-de-hmbyt5-bs8-wsFalse-e10-lr0.00016-poolingfirst-layers-1-crfFalse-2
|
55 |
+
[13]: https://hf.co/hmbench/hmbench-ajmc-de-hmbyt5-bs8-wsFalse-e10-lr0.00016-poolingfirst-layers-1-crfFalse-3
|
56 |
+
[14]: https://hf.co/hmbench/hmbench-ajmc-de-hmbyt5-bs8-wsFalse-e10-lr0.00016-poolingfirst-layers-1-crfFalse-4
|
57 |
+
[15]: https://hf.co/hmbench/hmbench-ajmc-de-hmbyt5-bs8-wsFalse-e10-lr0.00016-poolingfirst-layers-1-crfFalse-5
|
58 |
+
[16]: https://hf.co/hmbench/hmbench-ajmc-de-hmbyt5-bs8-wsFalse-e10-lr0.00015-poolingfirst-layers-1-crfFalse-1
|
59 |
+
[17]: https://hf.co/hmbench/hmbench-ajmc-de-hmbyt5-bs8-wsFalse-e10-lr0.00015-poolingfirst-layers-1-crfFalse-2
|
60 |
+
[18]: https://hf.co/hmbench/hmbench-ajmc-de-hmbyt5-bs8-wsFalse-e10-lr0.00015-poolingfirst-layers-1-crfFalse-3
|
61 |
+
[19]: https://hf.co/hmbench/hmbench-ajmc-de-hmbyt5-bs8-wsFalse-e10-lr0.00015-poolingfirst-layers-1-crfFalse-4
|
62 |
+
[20]: https://hf.co/hmbench/hmbench-ajmc-de-hmbyt5-bs8-wsFalse-e10-lr0.00015-poolingfirst-layers-1-crfFalse-5
|
63 |
+
|
64 |
+
The [training log](training.log) and TensorBoard logs are also uploaded to the model hub.
|
65 |
+
|
66 |
+
More information about fine-tuning can be found [here](https://github.com/stefan-it/hmBench).
|
67 |
+
|
68 |
+
# Acknowledgements
|
69 |
+
|
70 |
+
We thank [Luisa März](https://github.com/LuisaMaerz), [Katharina Schmid](https://github.com/schmika) and
|
71 |
+
[Erion Çano](https://github.com/erionc) for their fruitful discussions about Historic Language Models.
|
72 |
+
|
73 |
+
Research supported with Cloud TPUs from Google's [TPU Research Cloud](https://sites.research.google/trc/about/) (TRC).
|
74 |
+
Many Thanks for providing access to the TPUs ❤️
|