learning_rate: 1e-05
train_batch_size: 4
eval_batch_size: 4
seed: 552
gradient_accumulation_steps: 4
total_train_batch_size: 16
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: 0.05
num_epochs: 2

Training Loss	Epoch	Step	Validation Loss
-4.6212	0.0547	250	-1.3475
-27.3747	0.1094	500	-7.0080
-33.0028	0.1641	750	-8.7426
-51.24	0.2188	1000	-9.9981
-49.2631	0.2735	1250	-11.1210
-49.9911	0.3282	1500	-11.4823
-47.4685	0.3829	1750	-11.5264
-49.8516	0.4376	2000	-11.7210
-52.2479	0.4923	2250	-13.2389
-41.6111	0.5470	2500	-13.4486
-49.9071	0.6017	2750	-11.4862
-50.7067	0.6564	3000	-12.0170
-50.125	0.7111	3250	-13.8635
-64.6233	0.7658	3500	-12.3017
-62.0945	0.8205	3750	-13.0986
-51.1444	0.8752	4000	-13.6334

jnsffrt/instruct_mcq_contrastive_full_answer_no_rationale

instruct_contrastive