CoolFace
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silmi224/finetune-led-35000

sourceHugging Faceupdated 2y agoView on Hugging Face
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Model Card

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finetune-led-35000

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

  • —Loss: 1.8474
  • —Rouge1 Precision: 0.2576
  • —Rouge1 Recall: 0.3438
  • —Rouge1 Fmeasure: 0.2911

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
  • —trainbatchsize: 8
  • —evalbatchsize: 8
  • —seed: 42
  • —gradientaccumulationsteps: 4
  • —totaltrainbatch_size: 32
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —num_epochs: 2
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossRouge1 FmeasureRouge1 PrecisionRouge1 Recall
2.00010.01102.84440.27320.24840.3213
1.74090.01202.68950.26820.23750.3203
1.60960.02302.63350.27970.2460.3362
1.74520.03402.58170.2850.2510.3417
1.62120.03502.57650.28990.2530.3515
1.67430.04602.44250.27050.2410.3188
1.52290.04702.51460.28020.25010.3294
1.56810.05802.47850.26650.23020.3273
1.58110.06902.36220.2870.25770.3349
1.56420.061002.40530.27790.24490.3322
1.51750.071102.38180.28620.25770.3324
1.50730.081202.39300.29050.250.3587
1.53360.121302.36190.27550.24560.3242
1.51550.131402.36960.27520.2430.3284
1.51240.141502.32400.27880.24780.3296
1.51870.151602.28830.27390.24380.3225
1.46420.161702.30060.27690.24420.3307
1.65350.161802.27660.27160.24350.3165
1.49240.171902.30770.27820.24630.3303
1.52210.182002.27250.28290.25020.3357
1.3880.192102.25550.28110.25020.3305
1.51720.22202.25190.27580.24580.3243
1.4980.212302.25850.28090.24280.3437
1.4470.222402.21100.27450.24570.3206
1.46370.232502.25110.28540.2520.3395
1.50840.242602.20700.28760.25470.341
1.43470.252702.25580.28520.24930.344
1.31080.262802.24980.28150.24880.3349
1.38940.272902.23020.27940.24540.3347
1.43920.273002.20210.2760.24120.3327
1.37740.283102.19580.27630.2440.3286
1.36960.293202.16570.28110.25120.3292
1.41860.33302.15330.28070.2510.3288
1.30730.313402.18900.28050.24860.3324
1.35330.323502.16390.28360.25460.3302
1.36910.333602.12550.27650.250.3188
1.37160.343702.14360.28180.25120.3315
1.39850.353802.11600.28590.25550.3351
1.29930.363902.14170.27560.24420.3262
1.34530.374002.14590.28750.2560.3386
1.40360.374102.12000.28110.25060.33
1.37840.384202.08780.28850.25920.335
1.29230.394302.13420.28730.25350.3423
1.36290.44402.08870.28480.25460.3328
1.41510.414502.09050.28570.2540.3365
1.36790.424602.08290.2850.25250.3375
1.3390.434702.07860.27910.24520.334
1.42580.444802.07260.28770.26030.3317
1.40560.454902.09950.28910.25560.3428
1.35480.465002.06370.27570.24810.3199
1.32530.475102.06380.27940.250.3266
1.2640.485202.06090.28610.25870.3296
1.33070.485302.03960.28230.25590.3243
1.35360.495402.04640.28240.25320.3288
1.25920.55502.04800.28760.25920.3333
1.3580.515602.04320.28180.25280.3284
1.32270.525702.05600.28310.25020.3365
1.31890.535802.03110.28230.2510.3321
1.33670.545902.04980.2850.25380.335
1.34730.556002.06900.27730.24520.3292
1.28460.566102.05550.27960.24730.3321
1.30660.576202.06840.27990.2450.3366
1.31930.586302.04670.28520.25360.336
1.2690.596402.03810.28590.25610.3337
1.29060.596502.01910.28310.25140.3338
1.29810.66602.01840.27830.2490.3251
1.28880.616702.02950.28270.25150.3331
1.31790.626802.01210.28850.26110.333
1.33130.636902.02960.27390.24270.3245
1.17490.647002.04190.28090.25070.3298
1.30230.657102.02750.28380.25040.3379
1.2620.667201.99740.2860.25390.3378
1.29060.677301.98390.28390.2520.3357
1.240.687402.00410.2860.25280.3401
1.2390.697502.01160.27890.24550.3326
1.19720.697602.02930.28610.25360.3385
1.21140.77702.02710.27380.24360.322
1.27110.717802.00840.28810.25480.3417
1.2620.727901.99840.28060.24880.3322
1.26160.738001.97150.28560.25410.3364
1.27650.748101.97180.28250.24940.3356
1.21510.758201.99470.28570.25130.341
1.31650.768301.98540.28630.25240.3411
1.27040.778401.98580.29030.25690.3443
1.30320.788501.97740.29260.25830.3481
1.24610.798601.95960.28470.25560.3314
1.22880.88701.98730.28680.25470.339
1.22780.88801.97120.2890.25460.3455
1.21190.818901.98620.28220.24780.338
1.33630.829001.95550.28710.25760.3349
1.23240.839101.93940.28780.25880.3339
1.25280.849201.95930.28010.24980.3289
1.25720.859301.95000.28250.25070.3337
1.20450.869401.95860.29010.25890.3401
1.21730.879501.95510.2810.24870.3328
1.23150.889601.93070.28420.25330.3337
1.24450.899701.93620.28530.25370.336
1.24910.99801.96140.28290.24820.3397
1.30810.919901.95000.28570.25130.3411
1.19280.9110001.94390.28260.25140.333
1.22430.9210101.90740.28830.2590.3346
1.26620.9310201.91430.29120.25930.3422
1.22230.9410301.93420.28990.25810.3408
1.24990.9510401.93520.28350.25070.3366
1.33950.9610501.92840.28640.25480.3375
1.19080.9710601.94710.28530.25280.3376
1.24730.9810701.94620.29410.26130.3472
1.21390.9910801.93170.28590.25340.338
1.25341.010901.92780.29380.25940.3488
1.22041.0111001.91770.29120.25960.341
1.23991.0111101.92360.29030.25680.3443
1.15411.0211201.94410.28890.25480.3431
1.10381.0311301.92230.29250.26260.3399
1.11771.0411401.92440.28810.25650.338
1.12241.0511501.93240.28840.25470.3428
1.1041.0611601.91880.27980.24820.3304
1.1751.0711701.90420.29150.26180.3388
1.1021.0811801.93250.28530.2530.3372
1.08291.0911901.95030.28190.24780.3371
1.18421.112001.93600.27840.24380.3346
1.15521.1112101.90550.2860.2540.3369
1.12661.1212201.91060.2860.25550.3345
1.12881.1312301.90720.28650.25660.3336
1.17221.1312401.91140.28560.25390.3364
1.15141.1412501.91800.29060.25610.3461
1.16421.1512601.92260.29180.25710.3475
1.14641.1612701.90040.28190.25250.3283
1.18291.1712801.91810.29350.25680.3524
1.171.1812901.90310.28480.25230.3369
1.07511.1913001.93340.28750.25310.3428
1.13271.213101.89660.28910.25680.3407
1.13191.2113201.90760.29020.25750.3422
1.1061.2213301.89410.29080.2590.3413
1.17211.2313401.89560.29450.26090.3479
1.19641.2313501.91400.28510.25130.3389
1.11951.2413601.91680.29170.25610.3483
1.13521.2513701.89620.2860.2530.3389
1.11641.2613801.90500.29160.2580.3453
1.12191.2713901.90540.28720.25510.3386
1.15711.2814001.88450.28960.25740.3402
1.20331.2914101.89850.28520.25320.3362
1.11141.314201.89560.28820.25590.3395
1.12681.3114301.89550.28950.25630.3424
1.13471.3214401.88830.28650.25240.3412
1.03451.3314501.89600.28950.25710.3412
1.12311.3414601.88730.290.25750.3415
1.2361.3414701.87440.28980.25780.34
1.10541.3514801.88670.28840.25460.3425
1.13931.3614901.89070.29270.26050.344
1.10041.3715001.89530.2880.25430.3416
1.14821.3815101.87310.2880.25680.3377
1.17011.3915201.88680.28660.25250.3411
1.12331.415301.88030.28820.25620.3385
1.06851.4115401.88430.29350.2620.3433
1.06571.4215501.87480.28920.25530.3437
1.12751.4315601.88040.28810.25530.3405
1.08831.4415701.88030.28680.25270.3412
1.10961.4515801.88620.29270.25860.3472
1.15211.4515901.87240.2880.25640.3379
1.1421.4616001.87880.29260.25930.3454
1.04511.4716101.86840.28630.25710.3324
1.12941.4816201.87040.29020.25690.3427
1.16711.4916301.87560.29090.2590.3413
1.22521.516401.86180.29370.25990.347
1.08341.5116501.87760.29090.25890.3416
1.04171.5216601.86580.29110.25920.342
1.10361.5316701.87890.2890.25530.343
1.15751.5416801.86080.29270.25970.3452
1.0581.5516901.88040.29210.25850.3455
1.12511.5517001.86820.29730.26370.3503
1.08181.5617101.88000.28870.25440.3432
1.13461.5717201.85770.2890.25640.3404
1.10241.5817301.86810.29460.26080.3482
1.08231.5917401.86030.29080.25840.342
1.05621.617501.86700.29310.25840.3484
1.11281.6117601.85760.29260.26030.3439
1.07691.6217701.87090.29020.25680.3434
1.04221.6317801.85970.29110.25870.3425
1.19121.6417901.86480.29110.25740.3448
1.13491.6518001.86670.29330.26060.3453
1.11951.6618101.86840.28990.25680.3422
1.11861.6618201.85810.29080.25790.3434
1.07951.6718301.86390.29070.25610.3462
1.13941.6818401.84670.29290.26020.3446
1.07431.6918501.86820.2910.25850.3428
1.09541.718601.85040.29280.26030.3445
1.09381.7118701.86040.29160.25890.3436
1.10931.7218801.84270.28970.25810.3398
1.13991.7318901.87150.28910.25610.3422
1.15741.7419001.84480.28930.25680.3409
1.12441.7519101.85940.29270.25970.3453
1.12051.7619201.84920.29220.26060.3425
1.12181.7719301.85470.29060.25910.3401
1.12081.7719401.86050.29240.25880.3459
1.09831.7819501.84250.29330.26110.3442
1.19921.7919601.85870.29070.25650.3455
1.17241.819701.84130.29090.25760.3435
1.13441.8119801.84940.29040.25830.3413
1.14691.8219901.84630.29110.25810.3437
1.14911.8320001.85300.29050.25680.3441
1.09131.8420101.84930.29130.2580.3443
1.12981.8520201.84650.29050.25730.3433
1.12021.8620301.84880.28920.2560.3419
1.14391.8720401.84940.29110.25840.3428
1.03281.8720501.84690.29070.25820.3423
1.13471.8820601.84260.290.25760.341
1.0941.8920701.84800.29050.25770.3425
1.12011.920801.85420.28960.25680.3415
1.14751.9120901.85200.290.25740.3416
1.07931.9221001.85060.28970.25690.3414
1.06691.9321101.84840.29070.25770.3426
1.12761.9421201.84870.29040.25730.3427
1.09021.9521301.84870.29040.25750.3423
1.14491.9621401.84900.28980.25690.3419
1.11421.9721501.85050.290.25690.3424
1.14751.9821601.85010.28950.25610.3424
1.06631.9821701.84850.29060.25710.3434
1.14541.9921801.84750.29070.25730.3435

Framework versions

  • —Transformers 4.35.2
  • —Pytorch 2.1.1+cu121
  • —Datasets 2.14.5
  • —Tokenizers 0.15.1