BoolQ_Llama-3.2-1B-dlyt1wr4

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: 1.3222
• Model Preparation Time: 0.0041
• Mdl: 6237.6140
• Accumulated Loss: 4323.5846
• Correct Preds: 2327.0
• Total Preds: 3270.0
• Accuracy: 0.7116
• Correct Gen Preds: 2316.0
• Gen Accuracy: 0.7083
• Correct Gen Preds 9642: 1502.0
• Correct Preds 9642: 1512.0
• Total Labels 9642: 2026.0
• Accuracy 9642: 0.7463
• Gen Accuracy 9642: 0.7414
• Correct Gen Preds 2822: 805.0
• Correct Preds 2822: 815.0
• Total Labels 2822: 1231.0
• Accuracy 2822: 0.6621
• Gen Accuracy 2822: 0.6539

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: 32
• eval_batch_size: 120
• 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 9642	Correct Preds 9642	Total Labels 9642	Accuracy 9642	Gen Accuracy 9642	Correct Gen Preds 2822	Correct Preds 2822	Total Labels 2822	Accuracy 2822	Gen Accuracy 2822
No log	0	0	0.7080	0.0041	3339.8933	2315.0376	2032.0	3270.0	0.6214	2040.0	0.6239	2007.0	2008.0	2026.0	0.9911	0.9906	24.0	24.0	1231.0	0.0195	0.0195
0.7339	1.0	3	0.6871	0.0041	3241.5040	2246.8394	2049.0	3270.0	0.6266	1935.0	0.5917	1121.0	1187.0	2026.0	0.5859	0.5533	805.0	862.0	1231.0	0.7002	0.6539
0.2203	2.0	6	0.7155	0.0041	3375.4781	2339.7031	2151.0	3270.0	0.6578	1873.0	0.5728	1185.0	1356.0	2026.0	0.6693	0.5849	679.0	795.0	1231.0	0.6458	0.5516
0.0775	3.0	9	1.5181	0.0041	7161.7687	4964.1598	2122.0	3270.0	0.6489	2127.0	0.6505	1936.0	1938.0	2026.0	0.9566	0.9556	182.0	184.0	1231.0	0.1495	0.1478
0.0019	4.0	12	1.3222	0.0041	6237.6140	4323.5846	2327.0	3270.0	0.7116	2316.0	0.7083	1502.0	1512.0	2026.0	0.7463	0.7414	805.0	815.0	1231.0	0.6621	0.6539
0.0006	5.0	15	2.1361	0.0041	10077.3021	6985.0536	2195.0	3270.0	0.6713	2062.0	0.6306	1097.0	1185.0	2026.0	0.5849	0.5415	956.0	1010.0	1231.0	0.8205	0.7766
0.0001	6.0	18	2.5726	0.0041	12136.6096	8412.4567	2200.0	3270.0	0.6728	1960.0	0.5994	1078.0	1230.0	2026.0	0.6071	0.5321	873.0	970.0	1231.0	0.7880	0.7092
0.0001	7.0	21	2.8170	0.0041	13289.4765	9211.5632	2203.0	3270.0	0.6737	1910.0	0.5841	1086.0	1268.0	2026.0	0.6259	0.5360	815.0	935.0	1231.0	0.7595	0.6621
0.0	8.0	24	2.9660	0.0041	13992.3481	9698.7567	2207.0	3270.0	0.6749	1914.0	0.5853	1112.0	1287.0	2026.0	0.6352	0.5489	793.0	920.0	1231.0	0.7474	0.6442
0.0	9.0	27	3.0542	0.0041	14408.4594	9987.1830	2215.0	3270.0	0.6774	1939.0	0.5930	1141.0	1301.0	2026.0	0.6422	0.5632	789.0	914.0	1231.0	0.7425	0.6409
0.0	10.0	30	3.1077	0.0041	14661.1462	10162.3322	2211.0	3270.0	0.6761	1955.0	0.5979	1161.0	1305.0	2026.0	0.6441	0.5731	785.0	906.0	1231.0	0.7360	0.6377
0.0	11.0	33	3.1439	0.0041	14831.7314	10280.5728	2207.0	3270.0	0.6749	1970.0	0.6024	1170.0	1306.0	2026.0	0.6446	0.5775	791.0	901.0	1231.0	0.7319	0.6426
0.0	12.0	36	3.1697	0.0041	14953.5728	10365.0268	2207.0	3270.0	0.6749	1979.0	0.6052	1179.0	1310.0	2026.0	0.6466	0.5819	791.0	897.0	1231.0	0.7287	0.6426
0.0	13.0	39	3.1841	0.0041	15021.1170	10411.8449	2204.0	3270.0	0.6740	1990.0	0.6086	1186.0	1311.0	2026.0	0.6471	0.5854	795.0	893.0	1231.0	0.7254	0.6458
0.0	14.0	42	3.1923	0.0041	15060.2306	10438.9564	2207.0	3270.0	0.6749	1997.0	0.6107	1186.0	1313.0	2026.0	0.6481	0.5854	802.0	894.0	1231.0	0.7262	0.6515
0.0	15.0	45	3.2004	0.0041	15098.1299	10465.2261	2204.0	3270.0	0.6740	2012.0	0.6153	1195.0	1312.0	2026.0	0.6476	0.5898	808.0	892.0	1231.0	0.7246	0.6564
0.0	16.0	48	3.2018	0.0041	15105.0253	10470.0057	2207.0	3270.0	0.6749	2013.0	0.6156	1194.0	1312.0	2026.0	0.6476	0.5893	810.0	895.0	1231.0	0.7271	0.6580
0.0	17.0	51	3.2077	0.0041	15132.8760	10489.3104	2208.0	3270.0	0.6752	2020.0	0.6177	1200.0	1315.0	2026.0	0.6491	0.5923	811.0	893.0	1231.0	0.7254	0.6588
0.0	18.0	54	3.2123	0.0041	15154.4908	10504.2926	2206.0	3270.0	0.6746	2021.0	0.6180	1197.0	1313.0	2026.0	0.6481	0.5908	815.0	893.0	1231.0	0.7254	0.6621
0.0	19.0	57	3.2174	0.0041	15178.6611	10521.0462	2207.0	3270.0	0.6749	2024.0	0.6190	1201.0	1315.0	2026.0	0.6491	0.5928	814.0	892.0	1231.0	0.7246	0.6613
0.0	20.0	60	3.2183	0.0041	15182.4947	10523.7034	2211.0	3270.0	0.6761	2028.0	0.6202	1203.0	1318.0	2026.0	0.6505	0.5938	816.0	893.0	1231.0	0.7254	0.6629
0.0	21.0	63	3.2196	0.0041	15188.7486	10528.0383	2208.0	3270.0	0.6752	2026.0	0.6196	1201.0	1313.0	2026.0	0.6481	0.5928	816.0	895.0	1231.0	0.7271	0.6629
0.0	22.0	66	3.2239	0.0041	15208.9157	10542.0171	2204.0	3270.0	0.6740	2035.0	0.6223	1204.0	1315.0	2026.0	0.6491	0.5943	822.0	889.0	1231.0	0.7222	0.6677
0.0	23.0	69	3.2223	0.0041	15201.5672	10536.9235	2206.0	3270.0	0.6746	2030.0	0.6208	1202.0	1311.0	2026.0	0.6471	0.5933	819.0	895.0	1231.0	0.7271	0.6653
0.0	24.0	72	3.2266	0.0041	15221.7566	10550.9177	2206.0	3270.0	0.6746	2034.0	0.6220	1204.0	1312.0	2026.0	0.6476	0.5943	821.0	894.0	1231.0	0.7262	0.6669
0.0	25.0	75	3.2295	0.0041	15235.6263	10560.5314	2205.0	3270.0	0.6743	2039.0	0.6235	1208.0	1314.0	2026.0	0.6486	0.5962	822.0	891.0	1231.0	0.7238	0.6677
0.0	26.0	78	3.2290	0.0041	15233.1976	10558.8480	2210.0	3270.0	0.6758	2042.0	0.6245	1210.0	1317.0	2026.0	0.6500	0.5972	823.0	893.0	1231.0	0.7254	0.6686
0.0	27.0	81	3.2308	0.0041	15241.5995	10564.6717	2204.0	3270.0	0.6740	2044.0	0.6251	1208.0	1312.0	2026.0	0.6476	0.5962	827.0	892.0	1231.0	0.7246	0.6718
0.0	28.0	84	3.2303	0.0041	15239.1917	10563.0028	2209.0	3270.0	0.6755	2046.0	0.6257	1210.0	1316.0	2026.0	0.6496	0.5972	827.0	893.0	1231.0	0.7254	0.6718
0.0	29.0	87	3.2346	0.0041	15259.7713	10577.2675	2206.0	3270.0	0.6746	2051.0	0.6272	1214.0	1315.0	2026.0	0.6491	0.5992	828.0	891.0	1231.0	0.7238	0.6726
0.0	30.0	90	3.2359	0.0041	15265.6533	10581.3446	2207.0	3270.0	0.6749	2053.0	0.6278	1213.0	1315.0	2026.0	0.6491	0.5987	831.0	892.0	1231.0	0.7246	0.6751
0.0	31.0	93	3.2395	0.0041	15282.6219	10593.1063	2203.0	3270.0	0.6737	2059.0	0.6297	1215.0	1311.0	2026.0	0.6471	0.5997	835.0	892.0	1231.0	0.7246	0.6783
0.0	32.0	96	3.2376	0.0041	15273.6693	10586.9008	2204.0	3270.0	0.6740	2058.0	0.6294	1215.0	1312.0	2026.0	0.6476	0.5997	834.0	892.0	1231.0	0.7246	0.6775
0.0	33.0	99	3.2397	0.0041	15283.7410	10593.8820	2205.0	3270.0	0.6743	2065.0	0.6315	1221.0	1312.0	2026.0	0.6476	0.6027	835.0	893.0	1231.0	0.7254	0.6783
0.0	34.0	102	3.2420	0.0041	15294.5155	10601.3503	2204.0	3270.0	0.6740	2060.0	0.6300	1219.0	1313.0	2026.0	0.6481	0.6017	832.0	891.0	1231.0	0.7238	0.6759

Framework versions

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