learning_rate: 2e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
distributed_type: multi-GPU
num_devices: 8
total_train_batch_size: 256
total_eval_batch_size: 256
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10.0

Training Loss	Epoch	Step	Validation Loss	Mse	Target 0 Mse	Target 1 Mse	Target 2 Mse	Target 3 Mse
0.001	1.0	514	0.0005	0.0005	0.0013	0.0005	0.0001	0.0002
0.0011	2.0	1028	0.0005	0.0005	0.0012	0.0004	0.0001	0.0002
0.0006	3.0	1542	0.0004	0.0004	0.0011	0.0004	0.0001	0.0000
0.0004	4.0	2056	0.0004	0.0004	0.0010	0.0003	0.0001	0.0000
0.0004	5.0	2570	0.0004	0.0004	0.0010	0.0004	0.0001	0.0000
0.0003	6.0	3084	0.0004	0.0004	0.0010	0.0003	0.0001	0.0000
0.0004	7.0	3598	0.0004	0.0004	0.0010	0.0003	0.0001	0.0000
0.0004	8.0	4112	0.0003	0.0003	0.0010	0.0003	0.0001	0.0000
0.0003	9.0	4626	0.0003	0.0003	0.0010	0.0003	0.0001	0.0000
0.0004	10.0	5140	0.0003	0.0003	0.0010	0.0003	0.0001	0.0000

AlekseyKorshuk/twscrape-prepared-regression-e5-base-4k

twscrape-prepared-regression-e5-base-4k