learning_rate: 2e-05
train_batch_size: 4
eval_batch_size: 40
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.06
num_epochs: 10

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1 Macro	Accuracy Balanced	F1 Micro	Precision Macro	Recall Macro	Precision Micro	Recall Micro
0.697	1.0	654	0.6768	0.5908	0.3714	0.5	0.5908	0.2954	0.5	0.5908	0.5908
0.7267	2.0	1308	0.6543	0.5878	0.5797	0.6340	0.5878	0.6642	0.6340	0.5878	0.5878
0.7024	3.0	1962	0.9052	0.6779	0.6778	0.7044	0.6779	0.7076	0.7044	0.6779	0.6779
0.675	4.0	2616	1.1944	0.7206	0.7088	0.7073	0.7206	0.7108	0.7073	0.7206	0.7206
0.5142	5.0	3270	1.4177	0.7160	0.7097	0.7126	0.7160	0.7084	0.7126	0.7160	0.7160
0.3573	6.0	3924	1.6717	0.7267	0.7159	0.7148	0.7267	0.7172	0.7148	0.7267	0.7267
0.1643	7.0	4578	1.6307	0.7389	0.7295	0.7292	0.7389	0.7300	0.7292	0.7389	0.7389
0.1253	8.0	5232	1.8601	0.7374	0.7187	0.7141	0.7374	0.7331	0.7141	0.7374	0.7374
0.0937	9.0	5886	2.0865	0.7420	0.7209	0.7157	0.7420	0.7412	0.7157	0.7420	0.7420
0.0562	10.0	6540	2.1444	0.7389	0.7210	0.7165	0.7389	0.7342	0.7165	0.7389	0.7389

luissattelmayer/EuroBERT-immigration-stance-multiclass

EuroBERT-immigration-stance-positive