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: cosine
lr_scheduler_warmup_ratio: 0.01
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	Total Labels 36
No log	0	0	1.6389	0.006	706.9523	490.0220	66.0	299.0	0.2207	66.0	0.2207	62.0	62.0	64.0	0.9688	0.9688	0.0	0.0	73.0	0.0	0.0	4.0	4.0	78.0	0.0513	0.0513	0.0	0.0	83.0	0.0	0.0	1.0
1.7367	1.0	1	1.6389	0.006	706.9523	490.0220	66.0	299.0	0.2207	66.0	0.2207	62.0	62.0	64.0	0.9688	0.9688	0.0	0.0	73.0	0.0	0.0	4.0	4.0	78.0	0.0513	0.0513	0.0	0.0	83.0	0.0	0.0	1.0
1.7367	2.0	2	2.5849	0.006	1115.0583	772.8995	72.0	299.0	0.2408	63.0	0.2107	0.0	0.0	64.0	0.0	0.0	63.0	72.0	73.0	0.9863	0.8630	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.686	3.0	3	2.3954	0.006	1033.3076	716.2342	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	72.0	72.0	73.0	0.9863	0.9863	0.0	0.0	78.0	0.0	0.0	1.0	1.0	83.0	0.0120	0.0120	1.0
0.1308	4.0	4	3.5091	0.006	1513.7269	1049.2355	66.0	299.0	0.2207	34.0	0.1137	27.0	56.0	64.0	0.875	0.4219	6.0	8.0	73.0	0.1096	0.0822	0.0	0.0	78.0	0.0	0.0	1.0	2.0	83.0	0.0241	0.0120	1.0
0.0919	5.0	5	4.5350	0.006	1956.2548	1355.9725	72.0	299.0	0.2408	71.0	0.2375	1.0	2.0	64.0	0.0312	0.0156	70.0	70.0	73.0	0.9589	0.9589	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0008	6.0	6	5.9663	0.006	2573.6635	1783.9276	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0001	7.0	7	7.0163	0.006	3026.5888	2097.8715	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0	8.0	8	7.8549	0.006	3388.3437	2348.6208	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0	9.0	9	8.5290	0.006	3679.1101	2550.1648	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0	10.0	10	9.0813	0.006	3917.3504	2715.3004	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0	11.0	11	9.5223	0.006	4107.5735	2847.1530	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0	12.0	12	9.8450	0.006	4246.7775	2943.6418	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0	13.0	13	10.0820	0.006	4349.0238	3014.5136	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0	14.0	14	10.2630	0.006	4427.1048	3068.6352	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0	15.0	15	10.4135	0.006	4492.0237	3113.6335	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0	16.0	16	10.5454	0.006	4548.9178	3153.0696	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0	17.0	17	10.6501	0.006	4594.0917	3184.3817	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0	18.0	18	10.7377	0.006	4631.8710	3210.5683	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0	19.0	19	10.8058	0.006	4661.2653	3230.9429	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0	20.0	20	10.8522	0.006	4681.2829	3244.8181	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0	21.0	21	10.8886	0.006	4696.9714	3255.6925	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0	22.0	22	10.9239	0.006	4712.2095	3266.2547	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0	23.0	23	10.9471	0.006	4722.2182	3273.1922	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0	24.0	24	10.9741	0.006	4733.8499	3281.2547	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0	25.0	25	10.9917	0.006	4741.4235	3286.5043	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0	26.0	26	11.0067	0.006	4747.9153	3291.0041	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0	27.0	27	11.0245	0.006	4755.5791	3296.3162	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0	28.0	28	11.0307	0.006	4758.2846	3298.1916	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0	29.0	29	11.0362	0.006	4760.6287	3299.8163	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0	30.0	30	11.0439	0.006	4763.9649	3302.1288	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0	31.0	31	11.0487	0.006	4766.0390	3303.5665	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0	32.0	32	11.0546	0.006	4768.5629	3305.3159	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0
0.0	33.0	33	11.0604	0.006	4771.0883	3307.0664	73.0	299.0	0.2441	73.0	0.2441	0.0	0.0	64.0	0.0	0.0	73.0	73.0	73.0	1.0	1.0	0.0	0.0	78.0	0.0	0.0	0.0	0.0	83.0	0.0	0.0	1.0

Framework versions

Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1

donoway/ARC-Challenge_Llama-3.2-1B-4l8q8z7l

ARC-Challenge_Llama-3.2-1B-4l8q8z7l

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

donoway/
ARC-Challenge_Llama-3.2-1B-4l8q8z7l