stefan-it/autotrain-flair-georgian-ner-xlm_r_large-bs4-e10-lr5e-06-1

Fine-tuned English-Georgian NER Model with Flair

This Flair NER model was fine-tuned on the WikiANN dataset (Rahimi et al. splits) using XLM-R Large as backbone LM.

Notice: The dataset is very problematic, because it was automatically constructed.

We did manually inspect the development split of the Georgian data and found a lot of bad labeled examples, e.g. DVD ( 💿 ) as ORG.

Fine-Tuning

The latest Flair version is used for fine-tuning.

We use English and Georgian training splits for fine-tuning and the development set of Georgian for evaluation.

A hyper-parameter search over the following parameters with 5 different seeds per configuration is performed:

• Batch Sizes: [4]
• Learning Rates: [5e-06]

More details can be found in this repository.

Results

A hyper-parameter search with 5 different seeds per configuration is performed and micro F1-score on development set is reported:

Configuration	Seed 1	Seed 2	Seed 3	Seed 4	Seed 5	Average
bs4-e10-lr5e-06	0.9005	0.9012	0.9069	0.905	0.9048	0.9037 ± 0.0027

The result in bold shows the performance of this model.

Additionally, the Flair training log and TensorBoard logs are also uploaded to the model hub.