Fine-Tuning

The latest Flair version is used for fine-tuning.

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

More details can be found in this repository. All models are fine-tuned on a Hetzner GEX44 with an NVIDIA RTX 4000.

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
`bs8-e10-lr5e-05`	0.9477	0.935	0.9517	0.9443	0.9342	0.9426 ± 0.0077
`bs16-e10-lr5e-05`	0.9214	0.9364	0.9334	0.9489	0.9257	0.9332 ± 0.0106
`bs8-e10-lr3e-05`	0.928	0.9248	0.9421	0.9295	0.9263	0.9301 ± 0.0069
`bs16-e10-lr3e-05`	0.918	0.9256	0.9331	0.9273	0.9196	0.9247 ± 0.0061

The result in bold shows the performance of the current viewed model.

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