learning_rate: 3e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
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: 0.1
num_epochs: 20
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.6653	1.0	23	0.6820	0.7955	0.7805
0.5764	2.0	46	0.4134	0.9205	0.9213
0.3843	3.0	69	0.1825	0.9659	0.9677
0.2285	4.0	92	0.1695	0.9659	0.9677
0.1649	5.0	115	0.1108	0.9773	0.9787
0.1394	6.0	138	0.1390	0.9659	0.9677
0.1141	7.0	161	0.1329	0.9659	0.9677
0.0798	8.0	184	0.1043	0.9773	0.9787
0.0743	9.0	207	0.2201	0.9432	0.9451
0.0846	10.0	230	0.2657	0.9205	0.9213
0.0701	11.0	253	0.1470	0.9659	0.9677
0.082	12.0	276	0.1956	0.9545	0.9565
0.0145	13.0	299	0.1265	0.9773	0.9787
0.0191	14.0	322	0.1345	0.9773	0.9787
0.0355	15.0	345	0.1394	0.9773	0.9787
0.038	16.0	368	0.1432	0.9773	0.9787
0.0437	17.0	391	0.1467	0.9773	0.9787
0.0374	18.0	414	0.1494	0.9773	0.9787
0.0125	19.0	437	0.1511	0.9773	0.9787
0.0575	20.0	460	0.1517	0.9773	0.9787

ramesh070/mms-malayalam-binary

mms-malayalam-binary