learning_rate: 3e-05
train_batch_size: 1
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 8
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 30.0

Training Loss	Epoch	Step	Accuracy	F1	Validation Loss	Precision	Recall
0.6763	1.0	757	0.9843	0.7304	0.0400	0.6640	0.8115
0.2144	2.0	1514	0.9882	0.8050	0.0302	0.7767	0.8353
0.1276	3.0	2271	0.9889	0.7944	0.0272	0.7766	0.8131
0.0865	4.0	3028	0.9891	0.8207	0.0309	0.7947	0.8486
0.0529	5.0	3785	0.9882	0.8090	0.0341	0.7666	0.8564
0.0385	6.0	4542	0.9904	0.8383	0.0337	0.8094	0.8694
0.0212	7.0	5299	0.9901	0.8388	0.0384	0.8121	0.8673
0.0132	8.0	6056	0.9896	0.8273	0.0417	0.8002	0.8564
0.0088	9.0	6813	0.9897	0.8355	0.0473	0.8087	0.8641
0.0055	10.0	7570	0.9898	0.8375	0.0498	0.8078	0.8694
0.0346	11.0	8327	0.0458	0.7958	0.8668	0.8298	0.9891
0.0334	12.0	9084	0.0395	0.7841	0.8618	0.8211	0.9893
0.0241	13.0	9841	0.0433	0.8011	0.8544	0.8269	0.9887
0.0114	14.0	10598	0.0488	0.7874	0.8519	0.8184	0.9892
0.0102	15.0	11355	0.0500	0.8068	0.8698	0.8371	0.9897
0.0087	16.0	12112	0.0557	0.8107	0.8703	0.8395	0.9895
0.0070	17.0	12869	0.0620	0.8016	0.8735	0.8360	0.9892
0.0050	18.0	13626	0.0503	0.8074	0.8597	0.8327	0.9893
0.0089	19.0	14383	0.0561	0.8333	0.8592	0.8460	0.9899
0.0058	20.0	15140	0.0569	0.8051	0.8364	0.8205	0.9891
0.0030	21.0	15897	0.0581	0.8112	0.8682	0.8387	0.9900
0.0015	22.0	16654	0.0608	0.8206	0.8689	0.8441	0.9901
0.0004	23.0	17411	0.0633	0.8180	0.8645	0.8406	0.9899
0.0005	24.0	18168	0.0663	0.8195	0.8793	0.8484	0.9901
0.0001	25.0	18925	0.0705	0.8194	0.8887	0.8526	0.9901
0.0002	26.0	19682	0.0687	0.8254	0.8686	0.8464	0.9901
0.0002	27.0	20439	0.0695	0.8220	0.8784	0.8493	0.9901
0.0000	28.0	21196	0.0717	0.8253	0.8728	0.8484	0.9901
0.0001	29.0	21953	0.0735	0.8245	0.8776	0.8502	0.9901
0.0000	30.0	22710	0.0741	0.8254	0.8769	0.8503	0.9901

NER Performance Analysis

Evaluation Dataset

Model labels not present in the evaluation dataset were mapped to O: B-Gene, I-Gene

Entity	Precision	Recall	F1	Support
CopyNumberVariant	0.8283	0.8586	0.8432	191
DNAMutation	0.8597	0.8944	0.8767	322
ProteinMutation	0.9182	0.9359	0.9270	468
SNP	1.0000	0.9920	0.9960	375
micro avg	0.9132	0.9307	0.9218	1,356
macro avg	0.9016	0.9202	0.9107	1,356
weighted avg	0.9143	0.9307	0.9223	1,356

True \ Pred	O	CopyNumberVariant	DNAMutation	ProteinMutation	SNP
O	90,326	48	32	61	0
CopyNumberVariant	204	2,257	16	0	0
DNAMutation	56	0	1,543	14	0
ProteinMutation	78	0	7	1,528	0
SNP	11	0	0	0	1,544

Metric	Value
Model max sequence length	8192
Sequences classified as whole	383 / 383
Sequences truncated	0 / 383
Entities not fully evaluated due to truncation	0 / 1,356