Model description

More information needed

Intended uses & limitations

More information needed

More information needed

The following hyperparameters were used during training:

learning_rate: 3e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
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: cosine
lr_scheduler_warmup_ratio: 0.3
num_epochs: 20

Training Loss	Epoch	Step	Validation Loss	Accuracy
3.1723	1.0	22	1.6164	0.1923
2.8734	2.0	44	1.4347	0.3846
2.1553	3.0	66	1.1520	0.4808
1.6674	4.0	88	1.0921	0.4808
1.1204	5.0	110	0.9091	0.5962
1.0373	6.0	132	0.8185	0.6923
0.9181	7.0	154	0.9377	0.6731
0.7475	8.0	176	0.8407	0.6731
0.6679	9.0	198	0.9488	0.6923
0.4914	10.0	220	0.8699	0.7115
0.4421	11.0	242	1.1132	0.6538
0.3759	12.0	264	0.9250	0.7115
0.4317	13.0	286	0.9220	0.6731
0.4137	14.0	308	1.0225	0.7115
0.3451	15.0	330	1.0872	0.6538
0.3482	16.0	352	1.0129	0.6731
0.3346	17.0	374	1.0314	0.6538
0.3105	18.0	396	1.0348	0.6538
0.252	19.0	418	1.0386	0.6346
0.317	19.0930	420	1.0386	0.6346