Model description

More information needed

Intended uses & limitations

More information needed

More information needed

The following hyperparameters were used during training:

learning_rate: 0.0005
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
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: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
15.9975	1.0	125	nan	0.009	0.0126	0.0078	0.0084
0.0	2.0	250	nan	0.01	0.0001	0.01	0.0002
0.0	3.0	375	nan	0.01	0.0001	0.01	0.0002
0.0	4.0	500	nan	0.01	0.0001	0.01	0.0002
0.0	5.0	625	nan	0.01	0.0001	0.01	0.0002
0.0	6.0	750	nan	0.01	0.0001	0.01	0.0002
0.0	7.0	875	nan	0.01	0.0001	0.01	0.0002
0.0	8.0	1000	nan	0.01	0.0001	0.01	0.0002
0.0	9.0	1125	nan	0.01	0.0001	0.01	0.0002
0.0	10.0	1250	nan	0.01	0.0001	0.01	0.0002