flan-t5laa2-large

hrezaei/flan-t5laa2-large

flan-t5laa2-large is a feature extraction model from hrezaei. Use it when you need embeddings to search or compare text. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Feature Extraction
Library: transformers
Model type: t5la_adapter
Access: Public
Created: Nov 13, 2025
Updated: Nov 21, 2025
SHA: ab25e731

Datasets

HuggingFaceFW/fineweb

Model card

From the Hugging Face model README

flan-t5laa2-large

This model is a fine-tuned version of hrezaei/flan-t5laa2-large on the HuggingFaceFW/fineweb sample-350BT dataset. It achieves the following results on the evaluation set:

Perplexity: 1.1522
Loss: 0.1417
Accuracy: 0.0025
Lookahead Perplexity: 523.9169
Lookahead Loss: 6.2613
Base Perplexity: 1.1386
Base Loss: 0.1298

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: 5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
distributed_type: multi-GPU
num_devices: 2
total_train_batch_size: 32
total_eval_batch_size: 32
optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
training_steps: 524288

Training results

Training Loss	Epoch	Step	Accuracy	Base Loss	Base Perplexity	Lookahead Loss	Lookahead Perplexity	Validation Loss	Perplexity
0.3249	0.0095	5000	0.0025	0.1298	1.1386	9.1628	9536.0974	0.1473	1.1587
0.3149	0.0191	10000	0.0025	0.1298	1.1386	8.2987	4018.5587	0.1457	1.1568
0.3455	0.0286	15000	0.0025	0.1298	1.1386	7.8543	2576.7294	0.1448	1.1558
0.3164	0.0381	20000	0.0025	0.1298	1.1386	7.6043	2006.8105	0.1443	1.1552
0.3412	0.0477	25000	0.0025	0.1298	1.1386	7.4405	1703.6775	0.1440	1.1549
0.3334	0.0572	30000	0.0025	0.1298	1.1386	7.3224	1513.8265	0.1438	1.1546
0.3182	0.0668	35000	0.0025	0.1298	1.1386	7.2325	1383.6223	0.1436	1.1544
0.3193	0.0763	40000	0.0025	0.1298	1.1386	7.1599	1286.7995	0.1434	1.1542
0.3112	0.0858	45000	0.0025	0.1298	1.1386	7.1003	1212.3711	0.1433	1.1541
0.3084	0.0954	50000	0.0025	0.1298	1.1386	7.0527	1155.9677	0.1432	1.1540
0.3281	0.1049	55000	0.0025	0.1298	1.1386	7.0097	1107.3615	0.1431	1.1539
0.3096	0.1144	60000	0.0025	0.1298	1.1386	6.9716	1065.9302	0.1431	1.1538
0.3168	1.0048	65000	0.0025	0.1298	1.1386	6.9373	1029.9387	0.1430	1.1537
0.3158	1.0143	70000	0.0025	0.1298	1.1386	6.9058	998.0076	0.1429	1.1536
0.3149	1.0238	75000	0.0025	0.1298	1.1386	6.8755	968.2614	0.1429	1.1536
0.3185	1.0334	80000	0.0025	0.1298	1.1386	6.8495	943.4458	0.1428	1.1535
0.3247	1.0429	85000	0.0025	0.1298	1.1386	6.8251	920.7070	0.1428	1.1535
0.3166	1.0525	90000	0.0025	0.1298	1.1386	6.8033	900.7799	0.1427	1.1534
0.3171	1.0620	95000	0.0025	0.1298	1.1386	6.7802	880.2640	0.1427	1.1534
0.3247	1.0715	100000	0.0025	0.1298	1.1386	6.7589	861.6873	0.1426	1.1533
0.3199	1.0095	105000	0.0025	0.1298	1.1386	6.7393	844.9302	0.1426	1.1533
0.3116	1.0191	110000	0.0025	0.1298	1.1386	6.7202	828.9964	0.1426	1.1532
0.3431	1.0286	115000	0.0025	0.1298	1.1386	6.7028	814.7008	0.1425	1.1532
0.3145	1.0381	120000	0.0025	0.1298	1.1386	6.6864	801.3963	0.1425	1.1531
0.3396	1.0477	125000	0.0025	0.1298	1.1386	6.6714	789.4998	0.1425	1.1531
0.332	1.0572	130000	0.0025	0.1298	1.1386	6.6562	777.5850	0.1424	1.1531
0.3169	1.0668	135000	0.0025	0.1298	1.1386	6.6411	765.9321	0.1424	1.1530
0.3183	1.0763	140000	0.0025	0.1298	1.1386	6.6259	754.4168	0.1424	1.1530
0.3102	1.0858	145000	0.0025	0.1298	1.1386	6.6117	743.7487	0.1423	1.1530
0.3075	1.0954	150000	0.0025	0.1298	1.1386	6.6002	735.2481	0.1423	1.1530
0.3272	1.1049	155000	0.0025	0.1298	1.1386	6.5881	726.3988	0.1423	1.1529
0.3088	1.1144	160000	0.0025	0.1298	1.1386	6.5765	717.9999	0.1423	1.1529
0.316	2.0048	165000	0.0025	0.1298	1.1386	6.5648	709.6853	0.1423	1.1529
0.315	2.0143	170000	0.0025	0.1298	1.1386	6.5536	701.7924	0.1422	1.1528
0.3142	2.0238	175000	0.0025	0.1298	1.1386	6.5417	693.4763	0.1422	1.1528
0.3178	2.0334	180000	0.0025	0.1298	1.1386	6.5319	686.6713	0.1422	1.1528
0.324	2.0429	185000	0.0025	0.1298	1.1386	6.5221	680.0125	0.1422	1.1528
0.316	2.0525	190000	0.0025	0.1298	1.1386	6.5135	674.1869	0.1422	1.1528
0.3165	2.0620	195000	0.0025	0.1298	1.1386	6.5032	667.2772	0.1421	1.1527
0.3241	2.0715	200000	0.0025	0.1298	1.1386	6.4936	660.9243	0.1421	1.1527
0.3166	1.0095	205000	0.0025	0.1298	1.1386	6.4848	655.1015	0.1421	1.1527
0.3104	1.0191	210000	0.0025	0.1298	1.1386	6.4757	649.1789	0.1421	1.1527
0.3416	1.0286	215000	0.0025	0.1298	1.1386	6.4674	643.8252	0.1421	1.1526
0.3152	1.0381	220000	0.0025	0.1298	1.1386	6.4597	638.8783	0.1420	1.1526
0.3391	1.0477	225000	0.0025	0.1298	1.1386	6.4528	634.4516	0.1420	1.1526
0.3319	1.0572	230000	0.0025	0.1298	1.1386	6.4455	629.8329	0.1420	1.1526
0.3171	1.0668	235000	0.0025	0.1298	1.1386	6.4376	624.9101	0.1420	1.1526
0.3176	1.0763	240000	0.0025	0.1298	1.1386	6.4300	620.1895	0.1420	1.1526
0.3101	1.0858	245000	0.0025	0.1298	1.1386	6.4223	615.4315	0.1420	1.1526
0.3081	1.0954	250000	0.0025	0.1298	1.1386	6.4166	611.9308	0.1420	1.1525
0.3277	1.1049	255000	0.0025	0.1298	1.1386	6.4105	608.1798	0.1420	1.1525
0.3083	1.1144	260000	0.0025	0.1298	1.1386	6.4047	604.6944	0.1419	1.1525
0.3162	2.0048	265000	0.0025	0.1298	1.1386	6.3984	600.9119	0.1419	1.1525
0.3118	2.0143	270000	0.0025	0.1298	1.1386	6.3924	597.3080	0.1419	1.1525
0.314	2.0238	275000	0.0025	0.1298	1.1386	6.3858	593.3590	0.1419	1.1525
0.3149	2.0334	280000	0.0025	0.1298	1.1386	6.3805	590.2321	0.1419	1.1525
0.3232	2.0429	285000	0.0025	0.1298	1.1386	6.3752	587.1187	0.1419	1.1524
0.3179	2.0525	290000	0.0025	0.1298	1.1386	6.3707	584.4872	0.1419	1.1524
0.3149	2.0620	295000	0.0025	0.1298	1.1386	6.3652	581.2809	0.1419	1.1524
0.3259	2.0715	300000	0.0025	0.1298	1.1386	6.3602	578.3447	0.1419	1.1524
0.3389	2.0811	305000	0.0025	0.1298	1.1386	6.3549	575.3080	0.1418	1.1524
0.3119	2.0906	310000	0.0025	0.1298	1.1386	6.3502	572.6125	0.1418	1.1524
0.3149	2.1001	315000	0.0025	0.1298	1.1386	6.3465	570.4726	0.1418	1.1524
0.3289	2.1097	320000	0.0025	0.1298	1.1386	6.3422	568.0665	0.1418	1.1524
0.3111	2.1192	325000	0.0025	0.1298	1.1386	6.3381	565.7143	0.1418	1.1524
0.3179	3.0095	330000	0.0025	0.1298	1.1386	6.3341	563.4519	0.1418	1.1524
0.3094	3.0191	335000	0.0025	0.1298	1.1386	6.3298	561.0462	0.1418	1.1523
0.3396	3.0286	340000	0.0025	0.1298	1.1386	6.3259	558.8331	0.1418	1.1523
0.314	3.0381	345000	0.0025	0.1298	1.1386	6.3223	556.8332	0.1418	1.1523
0.3392	3.0477	350000	0.0025	0.1298	1.1386	6.3190	555.0390	0.1418	1.1523
0.3319	3.0572	355000	0.0025	0.1298	1.1386	6.3157	553.2072	0.1418	1.1523
0.3169	3.0668	360000	0.0025	0.1298	1.1386	6.3122	551.2481	0.1418	1.1523
0.3166	3.0763	365000	0.0025	0.1298	1.1386	6.3088	549.3597	0.1418	1.1523
0.3087	3.0858	370000	0.0025	0.1298	1.1386	6.3053	547.4488	0.1417	1.1523
0.3074	3.0954	375000	0.0025	0.1298	1.1386	6.3028	546.1247	0.1417	1.1523
0.3288	3.1049	380000	0.0025	0.1298	1.1386	6.3002	544.7043	0.1417	1.1523
0.3082	3.1144	385000	0.0025	0.1298	1.1386	6.2977	543.3141	0.1417	1.1523
0.3171	4.0048	390000	0.0025	0.1298	1.1386	6.2950	541.8326	0.1417	1.1523
0.3132	4.0143	395000	0.0025	0.1298	1.1386	6.2925	540.4888	0.1417	1.1523
0.3153	4.0238	400000	0.0025	0.1298	1.1386	6.2896	538.9527	0.1417	1.1523
0.317	4.0334	405000	0.0025	0.1298	1.1386	6.2874	537.7680	0.1417	1.1522
0.3161	1.0095	410000	1.1522	0.1417	0.0025	536.6438	6.2853	1.1386	0.1298
0.31	1.0191	415000	1.1522	0.1417	0.0025	535.4539	6.2831	1.1386	0.1298
0.3412	1.0286	420000	1.1522	0.1417	0.0025	534.3656	6.2811	1.1386	0.1298
0.3148	1.0381	425000	1.1522	0.1417	0.0025	533.3932	6.2793	1.1386	0.1298
0.3387	1.0477	430000	1.1522	0.1417	0.0025	532.5283	6.2776	1.1386	0.1298
0.3316	1.0572	435000	1.1522	0.1417	0.0025	531.6586	6.2760	1.1386	0.1298
0.3168	1.0668	440000	1.1522	0.1417	0.0025	530.7140	6.2742	1.1386	0.1298
0.3173	1.0763	445000	1.1522	0.1417	0.0025	529.8676	6.2726	1.1386	0.1298
0.3098	1.0858	450000	1.1522	0.1417	0.0025	529.0170	6.2710	1.1386	0.1298
0.3078	1.0954	455000	1.1522	0.1417	0.0025	528.4528	6.2700	1.1386	0.1298
0.3274	1.1049	460000	1.1522	0.1417	0.0025	527.8631	6.2688	1.1386	0.1298
0.308	1.1144	465000	1.1522	0.1417	0.0025	527.3422	6.2678	1.1386	0.1298
0.3159	2.0048	470000	1.1522	0.1417	0.0025	526.7932	6.2668	1.1386	0.1298
0.3115	2.0143	475000	1.1522	0.1417	0.0025	526.2932	6.2659	1.1386	0.1298
0.3137	2.0238	480000	1.1522	0.1417	0.0025	525.7652	6.2649	1.1386	0.1298
0.3146	2.0334	485000	1.1522	0.1417	0.0025	525.3872	6.2641	1.1386	0.1298
0.323	2.0429	490000	1.1522	0.1417	0.0025	525.0387	6.2635	1.1386	0.1298
0.3177	2.0525	495000	1.1522	0.1417	0.0025	524.7778	6.2630	1.1386	0.1298
0.3147	2.0620	500000	1.1522	0.1417	0.0025	524.4927	6.2624	1.1386	0.1298
0.3257	2.0715	505000	1.1522	0.1417	0.0025	524.2781	6.2620	1.1386	0.1298
0.3387	2.0811	510000	1.1522	0.1417	0.0025	524.1006	6.2617	1.1386	0.1298
0.3117	2.0906	515000	1.1522	0.1417	0.0025	523.9845	6.2615	1.1386	0.1298
0.3147	2.1001	520000	1.1522	0.1417	0.0025	523.9337	6.2614	1.1386	0.1298

Framework versions

Transformers 4.57.0.dev0
Pytorch 2.8.0+cu128
Datasets 4.2.0
Tokenizers 0.22.1

Task: Feature Extraction
Library: transformers
Type: t5la_adapter
Created: Nov 13, 2025
Updated: Nov 21, 2025