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_FUSED 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: 15
mixed_precision_training: Native AMP
label_smoothing_factor: 0.1

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	170	2.8936	0.4647	0.3646
No log	2.0	340	1.7200	0.7224	0.6580
2.6315	3.0	510	1.4805	0.7784	0.7387
2.6315	4.0	680	1.3844	0.7982	0.7736
2.6315	5.0	850	1.3450	0.8115	0.7967
1.1794	6.0	1020	1.3594	0.8078	0.7919
1.1794	7.0	1190	1.3484	0.8137	0.8032
1.1794	8.0	1360	1.3337	0.8373	0.8272
0.9009	9.0	1530	1.3531	0.8321	0.8234
0.9009	10.0	1700	1.3591	0.8402	0.8311
0.9009	11.0	1870	1.3585	0.8409	0.8305

denizzay/sabanci-it-destek-v1

sabanci-it-destek-v1