learning_rate: 1e-05
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: cosine
lr_scheduler_warmup_ratio: 0.1
training_steps: 1500
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	2	2.6128	0.0036	0.0475	0.0067	0.0087
No log	2.0	4	2.6071	0.0036	0.0475	0.0067	0.0087
No log	3.0	6	2.5970	0.0034	0.0447	0.0063	0.0087
No log	4.0	8	2.5823	0.0036	0.0475	0.0067	0.0089
No log	5.0	10	2.5632	0.0041	0.0531	0.0075	0.0092
No log	6.0	12	2.5395	0.0045	0.0587	0.0084	0.0100
No log	7.0	14	2.5113	0.0045	0.0587	0.0084	0.0110
No log	8.0	16	2.4784	0.0046	0.0587	0.0085	0.0135
No log	9.0	18	2.4407	0.0044	0.0559	0.0082	0.0189
No log	10.0	20	2.3978	0.0045	0.0559	0.0083	0.0296
No log	11.0	22	2.3493	0.0049	0.0587	0.0090	0.0569

Giannis17/layoutlmv3-finetuned-invoice_ConControl_v300

layoutlmv3-finetuned-invoice_ConControl_v3