learning_rate: 1e-05
train_batch_size: 8
eval_batch_size: 8
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_steps: 500
num_epochs: 25
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
2.4495	1.3514	50	2.5136	0.0556	0.0522	0.1279	0.0556
2.4414	2.7027	100	2.5005	0.0714	0.0678	0.0799	0.0714
2.4231	4.0541	150	2.4821	0.0714	0.0718	0.0911	0.0714
2.3702	5.4054	200	2.4614	0.0873	0.0946	0.1167	0.0873
2.3442	6.7568	250	2.4363	0.0714	0.0651	0.0683	0.0714
2.271	8.1081	300	2.3787	0.1349	0.1268	0.1264	0.1349
2.1474	9.4595	350	2.2815	0.1746	0.1619	0.1687	0.1746
1.9343	10.8108	400	2.0912	0.3413	0.3320	0.3770	0.3413
1.6174	12.1622	450	1.8072	0.4524	0.4455	0.5545	0.4524
1.1783	13.5135	500	1.4265	0.6111	0.6193	0.6449	0.6111
0.7923	14.8649	550	1.1770	0.6905	0.6985	0.7139	0.6905
0.4365	16.2162	600	1.0497	0.7143	0.7147	0.7417	0.7143
0.2509	17.5676	650	0.9858	0.7460	0.7486	0.7734	0.7460
0.1531	18.9189	700	0.9514	0.7460	0.7506	0.7804	0.7460
0.0923	20.2703	750	0.9163	0.7698	0.7709	0.7911	0.7698
0.0653	21.6216	800	0.9064	0.7778	0.7797	0.7978	0.7778
0.0509	22.9730	850	0.9130	0.7778	0.7801	0.8004	0.7778
0.04	24.3243	900	0.9001	0.7778	0.7818	0.8035	0.7778

Heather-Driver/distilbert-classn-LAlg-multihead-context-width-4

distilbert-classn-LAlg-multihead-context-width-4