ARC-Easy_Llama-3.2-1B-ro2gi4y6

This model is a fine-tuned version of meta-llama/Llama-3.2-1B on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.6994
• Model Preparation Time: 0.0055
• Mdl: 1397.4674
• Accumulated Loss: 968.6506
• Correct Preds: 430.0
• Total Preds: 570.0
• Accuracy: 0.7544
• Correct Gen Preds: 430.0
• Gen Accuracy: 0.7544
• Correct Gen Preds 32: 118.0
• Correct Preds 32: 118.0
• Total Labels 32: 158.0
• Accuracy 32: 0.7468
• Gen Accuracy 32: 0.7468
• Correct Gen Preds 33: 116.0
• Correct Preds 33: 116.0
• Total Labels 33: 152.0
• Accuracy 33: 0.7632
• Gen Accuracy 33: 0.7632
• Correct Gen Preds 34: 113.0
• Correct Preds 34: 113.0
• Total Labels 34: 142.0
• Accuracy 34: 0.7958
• Gen Accuracy 34: 0.7958
• Correct Gen Preds 35: 83.0
• Correct Preds 35: 83.0
• Total Labels 35: 118.0
• Accuracy 35: 0.7034
• Gen Accuracy 35: 0.7034
• Correct Gen Preds 36: 0.0
• Correct Preds 36: 0.0
• Total Labels 36: 0.0
• Accuracy 36: 0.0
• Gen Accuracy 36: 0.0

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• 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	Correct Gen Preds 36	Correct Preds 36	Total Labels 36	Accuracy 36	Gen Accuracy 36
No log	0	0	1.5354	0.0055	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	0.0	0.0	0.0	0.0	0.0
1.1499	1.0	30	0.9537	0.0055	784.2818	543.6227	379.0	570.0	0.6649	377.0	0.6614	127.0	128.0	158.0	0.8101	0.8038	85.0	86.0	152.0	0.5658	0.5592	96.0	96.0	142.0	0.6761	0.6761	69.0	69.0	118.0	0.5847	0.5847	0.0	0.0	0.0	0.0	0.0
0.3791	2.0	60	0.7650	0.0055	629.1242	436.0757	425.0	570.0	0.7456	424.0	0.7439	109.0	110.0	158.0	0.6962	0.6899	123.0	123.0	152.0	0.8092	0.8092	106.0	106.0	142.0	0.7465	0.7465	86.0	86.0	118.0	0.7288	0.7288	0.0	0.0	0.0	0.0	0.0
0.2137	3.0	90	0.9976	0.0055	820.3431	568.6185	414.0	570.0	0.7263	414.0	0.7263	98.0	98.0	158.0	0.6203	0.6203	119.0	119.0	152.0	0.7829	0.7829	115.0	115.0	142.0	0.8099	0.8099	82.0	82.0	118.0	0.6949	0.6949	0.0	0.0	0.0	0.0	0.0
0.153	4.0	120	1.5820	0.0055	1300.9342	901.7389	419.0	570.0	0.7351	416.0	0.7298	112.0	115.0	158.0	0.7278	0.7089	113.0	113.0	152.0	0.7434	0.7434	120.0	120.0	142.0	0.8451	0.8451	71.0	71.0	118.0	0.6017	0.6017	0.0	0.0	0.0	0.0	0.0
0.0002	5.0	150	1.9407	0.0055	1595.9007	1106.1941	425.0	570.0	0.7456	423.0	0.7421	111.0	112.0	158.0	0.7089	0.7025	126.0	127.0	152.0	0.8355	0.8289	110.0	110.0	142.0	0.7746	0.7746	76.0	76.0	118.0	0.6441	0.6441	0.0	0.0	0.0	0.0	0.0
0.0034	6.0	180	1.6994	0.0055	1397.4674	968.6506	430.0	570.0	0.7544	430.0	0.7544	118.0	118.0	158.0	0.7468	0.7468	116.0	116.0	152.0	0.7632	0.7632	113.0	113.0	142.0	0.7958	0.7958	83.0	83.0	118.0	0.7034	0.7034	0.0	0.0	0.0	0.0	0.0
0.0002	7.0	210	2.0344	0.0055	1672.9333	1159.5890	430.0	570.0	0.7544	430.0	0.7544	117.0	117.0	158.0	0.7405	0.7405	111.0	111.0	152.0	0.7303	0.7303	118.0	118.0	142.0	0.8310	0.8310	84.0	84.0	118.0	0.7119	0.7119	0.0	0.0	0.0	0.0	0.0
0.2384	8.0	240	2.3318	0.0055	1917.5151	1329.1202	422.0	570.0	0.7404	421.0	0.7386	117.0	118.0	158.0	0.7468	0.7405	111.0	111.0	152.0	0.7303	0.7303	113.0	113.0	142.0	0.7958	0.7958	80.0	80.0	118.0	0.6780	0.6780	0.0	0.0	0.0	0.0	0.0
0.0001	9.0	270	2.3574	0.0055	1938.6154	1343.7458	426.0	570.0	0.7474	426.0	0.7474	112.0	112.0	158.0	0.7089	0.7089	114.0	114.0	152.0	0.75	0.75	115.0	115.0	142.0	0.8099	0.8099	85.0	85.0	118.0	0.7203	0.7203	0.0	0.0	0.0	0.0	0.0
0.0039	10.0	300	2.6388	0.0055	2169.9437	1504.0904	422.0	570.0	0.7404	421.0	0.7386	109.0	110.0	158.0	0.6962	0.6899	115.0	115.0	152.0	0.7566	0.7566	111.0	111.0	142.0	0.7817	0.7817	86.0	86.0	118.0	0.7288	0.7288	0.0	0.0	0.0	0.0	0.0
0.0	11.0	330	2.5992	0.0055	2137.4472	1481.5655	421.0	570.0	0.7386	420.0	0.7368	110.0	111.0	158.0	0.7025	0.6962	115.0	115.0	152.0	0.7566	0.7566	115.0	115.0	142.0	0.8099	0.8099	80.0	80.0	118.0	0.6780	0.6780	0.0	0.0	0.0	0.0	0.0
0.0	12.0	360	2.5923	0.0055	2131.7646	1477.6266	422.0	570.0	0.7404	421.0	0.7386	108.0	109.0	158.0	0.6899	0.6835	113.0	113.0	152.0	0.7434	0.7434	114.0	114.0	142.0	0.8028	0.8028	86.0	86.0	118.0	0.7288	0.7288	0.0	0.0	0.0	0.0	0.0
0.0	13.0	390	2.6003	0.0055	2138.2906	1482.1501	423.0	570.0	0.7421	422.0	0.7404	113.0	114.0	158.0	0.7215	0.7152	111.0	111.0	152.0	0.7303	0.7303	114.0	114.0	142.0	0.8028	0.8028	84.0	84.0	118.0	0.7119	0.7119	0.0	0.0	0.0	0.0	0.0
0.0	14.0	420	2.6367	0.0055	2168.2271	1502.9005	423.0	570.0	0.7421	422.0	0.7404	115.0	116.0	158.0	0.7342	0.7278	111.0	111.0	152.0	0.7303	0.7303	113.0	113.0	142.0	0.7958	0.7958	83.0	83.0	118.0	0.7034	0.7034	0.0	0.0	0.0	0.0	0.0
0.0	15.0	450	2.6527	0.0055	2181.4382	1512.0577	424.0	570.0	0.7439	423.0	0.7421	113.0	114.0	158.0	0.7215	0.7152	112.0	112.0	152.0	0.7368	0.7368	114.0	114.0	142.0	0.8028	0.8028	84.0	84.0	118.0	0.7119	0.7119	0.0	0.0	0.0	0.0	0.0
0.0	16.0	480	2.6577	0.0055	2185.4872	1514.8643	423.0	570.0	0.7421	422.0	0.7404	113.0	114.0	158.0	0.7215	0.7152	111.0	111.0	152.0	0.7303	0.7303	114.0	114.0	142.0	0.8028	0.8028	84.0	84.0	118.0	0.7119	0.7119	0.0	0.0	0.0	0.0	0.0
0.0	17.0	510	2.6565	0.0055	2184.5381	1514.2064	423.0	570.0	0.7421	422.0	0.7404	114.0	115.0	158.0	0.7278	0.7215	111.0	111.0	152.0	0.7303	0.7303	113.0	113.0	142.0	0.7958	0.7958	84.0	84.0	118.0	0.7119	0.7119	0.0	0.0	0.0	0.0	0.0

Framework versions

• Transformers 4.51.3
• Pytorch 2.6.0+cu124
• Datasets 3.5.0
• Tokenizers 0.21.1