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	0.0056	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
0.7932	1.0	23	0.8627	0.0056	709.4533	491.7556	400.0	570.0	0.7018	400.0	0.7018	89.0	89.0	158.0	0.5633	0.5633	110.0	110.0	152.0	0.7237	0.7237	114.0	114.0	142.0	0.8028	0.8028	87.0	87.0	118.0	0.7373	0.7373
0.3059	2.0	46	0.7544	0.0056	620.3674	430.0059	420.0	570.0	0.7368	420.0	0.7368	131.0	131.0	158.0	0.8291	0.8291	99.0	99.0	152.0	0.6513	0.6513	110.0	110.0	142.0	0.7746	0.7746	80.0	80.0	118.0	0.6780	0.6780
0.0715	3.0	69	0.7862	0.0056	646.5485	448.1532	433.0	570.0	0.7596	432.0	0.7579	121.0	122.0	158.0	0.7722	0.7658	115.0	115.0	152.0	0.7566	0.7566	112.0	112.0	142.0	0.7887	0.7887	84.0	84.0	118.0	0.7119	0.7119
0.0471	4.0	92	0.9520	0.0056	782.8276	542.6148	421.0	570.0	0.7386	421.0	0.7386	116.0	116.0	158.0	0.7342	0.7342	115.0	115.0	152.0	0.7566	0.7566	113.0	113.0	142.0	0.7958	0.7958	77.0	77.0	118.0	0.6525	0.6525
0.0009	5.0	115	1.6365	0.0056	1345.7469	932.8006	412.0	570.0	0.7228	400.0	0.7018	118.0	121.0	158.0	0.7658	0.7468	108.0	113.0	152.0	0.7434	0.7105	102.0	102.0	142.0	0.7183	0.7183	72.0	76.0	118.0	0.6441	0.6102
0.0	6.0	138	2.5894	0.0056	2129.3265	1475.9367	423.0	570.0	0.7421	423.0	0.7421	115.0	115.0	158.0	0.7278	0.7278	119.0	119.0	152.0	0.7829	0.7829	114.0	114.0	142.0	0.8028	0.8028	75.0	75.0	118.0	0.6356	0.6356
0.0	7.0	161	2.2776	0.0056	1872.9361	1298.2204	420.0	570.0	0.7368	420.0	0.7368	117.0	117.0	158.0	0.7405	0.7405	112.0	112.0	152.0	0.7368	0.7368	114.0	114.0	142.0	0.8028	0.8028	77.0	77.0	118.0	0.6525	0.6525
0.4941	8.0	184	2.6439	0.0056	2174.2051	1507.0441	414.0	570.0	0.7263	414.0	0.7263	112.0	112.0	158.0	0.7089	0.7089	113.0	113.0	152.0	0.7434	0.7434	112.0	112.0	142.0	0.7887	0.7887	77.0	77.0	118.0	0.6525	0.6525
0.0	9.0	207	2.7489	0.0056	2260.5335	1566.8824	418.0	570.0	0.7333	418.0	0.7333	112.0	112.0	158.0	0.7089	0.7089	110.0	110.0	152.0	0.7237	0.7237	117.0	117.0	142.0	0.8239	0.8239	79.0	79.0	118.0	0.6695	0.6695
0.0	10.0	230	2.7904	0.0056	2294.6851	1590.5545	416.0	570.0	0.7298	416.0	0.7298	111.0	111.0	158.0	0.7025	0.7025	109.0	109.0	152.0	0.7171	0.7171	117.0	117.0	142.0	0.8239	0.8239	79.0	79.0	118.0	0.6695	0.6695
0.0	11.0	253	2.8203	0.0056	2319.2139	1607.5566	416.0	570.0	0.7298	416.0	0.7298	112.0	112.0	158.0	0.7089	0.7089	108.0	108.0	152.0	0.7105	0.7105	118.0	118.0	142.0	0.8310	0.8310	78.0	78.0	118.0	0.6610	0.6610
0.0	12.0	276	2.8184	0.0056	2317.6855	1606.4971	414.0	570.0	0.7263	414.0	0.7263	111.0	111.0	158.0	0.7025	0.7025	108.0	108.0	152.0	0.7105	0.7105	116.0	116.0	142.0	0.8169	0.8169	79.0	79.0	118.0	0.6695	0.6695
0.0	13.0	299	2.8234	0.0056	2321.7853	1609.3389	415.0	570.0	0.7281	415.0	0.7281	111.0	111.0	158.0	0.7025	0.7025	110.0	110.0	152.0	0.7237	0.7237	116.0	116.0	142.0	0.8169	0.8169	78.0	78.0	118.0	0.6610	0.6610
0.0	14.0	322	2.8142	0.0056	2314.1965	1604.0788	419.0	570.0	0.7351	419.0	0.7351	112.0	112.0	158.0	0.7089	0.7089	111.0	111.0	152.0	0.7303	0.7303	117.0	117.0	142.0	0.8239	0.8239	79.0	79.0	118.0	0.6695	0.6695
0.0	15.0	345	2.8539	0.0056	2346.8664	1626.7238	417.0	570.0	0.7316	417.0	0.7316	112.0	112.0	158.0	0.7089	0.7089	109.0	109.0	152.0	0.7171	0.7171	117.0	117.0	142.0	0.8239	0.8239	79.0	79.0	118.0	0.6695	0.6695
0.0	16.0	368	2.8455	0.0056	2339.9570	1621.9346	416.0	570.0	0.7298	416.0	0.7298	112.0	112.0	158.0	0.7089	0.7089	109.0	109.0	152.0	0.7171	0.7171	117.0	117.0	142.0	0.8239	0.8239	78.0	78.0	118.0	0.6610	0.6610
0.0	17.0	391	2.8536	0.0056	2346.6002	1626.5393	416.0	570.0	0.7298	416.0	0.7298	112.0	112.0	158.0	0.7089	0.7089	109.0	109.0	152.0	0.7171	0.7171	116.0	116.0	142.0	0.8169	0.8169	79.0	79.0	118.0	0.6695	0.6695
0.0	18.0	414	2.8545	0.0056	2347.3379	1627.0506	417.0	570.0	0.7316	417.0	0.7316	112.0	112.0	158.0	0.7089	0.7089	110.0	110.0	152.0	0.7237	0.7237	116.0	116.0	142.0	0.8169	0.8169	79.0	79.0	118.0	0.6695	0.6695

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-4ilji8pe

ARC-Easy_Llama-3.2-1B-4ilji8pe

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

donoway/
ARC-Easy_Llama-3.2-1B-4ilji8pe