learning_rate: 2e-05
train_batch_size: 64
eval_batch_size: 112
seed: 42
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: constant
lr_scheduler_warmup_ratio: 0.001
num_epochs: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Model Preparation Time	Mdl	Accumulated Loss	Correct Preds	Total Preds	Accuracy	Correct Gen Preds	Gen Accuracy	Correct Gen Preds 32	Correct Preds 32	Total Labels 32	Accuracy 32	Gen Accuracy 32	Correct Gen Preds 33	Correct Preds 33	Total Labels 33	Accuracy 33	Gen Accuracy 33	Correct Gen Preds 34	Correct Preds 34	Total Labels 34	Accuracy 34	Gen Accuracy 34	Correct Gen Preds 35	Correct Preds 35	Total Labels 35	Accuracy 35	Gen Accuracy 35
No log	0	0	1.5354	0.0058	1262.6022	875.1692	172.0	570.0	0.3018	170.0	0.2982	154.0	154.0	158.0	0.9747	0.9747	0.0	0.0	152.0	0.0	0.0	15.0	17.0	142.0	0.1197	0.1056	1.0	1.0	118.0	0.0085	0.0085
0.7074	1.0	18	0.8427	0.0058	692.9715	480.3312	397.0	570.0	0.6965	397.0	0.6965	120.0	120.0	158.0	0.7595	0.7595	108.0	108.0	152.0	0.7105	0.7105	107.0	107.0	142.0	0.7535	0.7535	62.0	62.0	118.0	0.5254	0.5254
0.6643	2.0	36	0.8207	0.0058	674.9187	467.8180	409.0	570.0	0.7175	408.0	0.7158	120.0	121.0	158.0	0.7658	0.7595	107.0	107.0	152.0	0.7039	0.7039	105.0	105.0	142.0	0.7394	0.7394	76.0	76.0	118.0	0.6441	0.6441
0.3128	3.0	54	0.9661	0.0058	794.4409	550.6645	413.0	570.0	0.7246	413.0	0.7246	107.0	107.0	158.0	0.6772	0.6772	123.0	123.0	152.0	0.8092	0.8092	115.0	115.0	142.0	0.8099	0.8099	68.0	68.0	118.0	0.5763	0.5763
0.0188	4.0	72	1.6770	0.0058	1379.0355	955.8746	393.0	570.0	0.6895	382.0	0.6702	116.0	119.0	158.0	0.7532	0.7342	92.0	96.0	152.0	0.6316	0.6053	93.0	95.0	142.0	0.6690	0.6549	81.0	83.0	118.0	0.7034	0.6864
0.0039	5.0	90	1.7465	0.0058	1436.2032	995.5002	410.0	570.0	0.7193	410.0	0.7193	112.0	112.0	158.0	0.7089	0.7089	120.0	120.0	152.0	0.7895	0.7895	99.0	99.0	142.0	0.6972	0.6972	79.0	79.0	118.0	0.6695	0.6695
0.0012	6.0	108	2.0934	0.0058	1721.4997	1193.2527	404.0	570.0	0.7088	404.0	0.7088	111.0	111.0	158.0	0.7025	0.7025	97.0	97.0	152.0	0.6382	0.6382	114.0	114.0	142.0	0.8028	0.8028	82.0	82.0	118.0	0.6949	0.6949
0.0001	7.0	126	2.4513	0.0058	2015.7579	1397.2169	406.0	570.0	0.7123	405.0	0.7105	118.0	118.0	158.0	0.7468	0.7468	107.0	107.0	152.0	0.7039	0.7039	108.0	108.0	142.0	0.7606	0.7606	72.0	73.0	118.0	0.6186	0.6102

Framework versions

Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1

donoway/ARC-Easy_Llama-3.2-1B-9odgjccg

ARC-Easy_Llama-3.2-1B-9odgjccg

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

donoway/
ARC-Easy_Llama-3.2-1B-9odgjccg