CoolFace
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simon-muenker/TWON-Agent-OSN-Replies-en

sourceHugging Facellama3.2updated 1y agoView on Hugging Face
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Model Card

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TWON-Agent-OSN-Replies-en

This model is a fine-tuned version of meta-llama/Llama-3.2-3B-Instruct on the generator dataset. It achieves the following results on the evaluation set:

  • —Loss: 1.8358

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: 4
  • —evalbatchsize: 8
  • —seed: 42
  • —optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • —lrschedulertype: linear
  • —num_epochs: 8

Training results

Training LossEpochStepValidation Loss
2.35030.04972002.1682
2.10360.09944002.1058
1.96490.14916002.0560
1.83960.19888002.0452
1.72760.248410002.0329
1.65240.298112002.0138
1.56450.347814002.0187
1.48010.397516001.9912
1.40050.447218001.9669
1.35870.496920001.9804
1.29210.546622001.9398
1.23970.596324001.9562
1.19290.646026001.9550
1.13040.695728001.9113
1.08990.745330001.9063
1.05530.795032001.9009
1.03140.844734001.8910
0.99990.894436001.9052
0.96090.944138001.8723
0.96280.993840001.9101
0.93341.043542001.9030
0.92481.093244001.9266
0.89261.142946001.8806
0.85711.192548001.8865
0.83071.242250001.9113
0.78431.291952001.9155
0.78051.341654001.8569
0.8121.391356001.8873
0.77831.441058001.8931
0.74891.490760001.8741
0.73861.540462001.8477
0.72171.590164001.8675
0.71771.639866001.8315
0.70511.689468001.8340
0.68481.739170001.8802
0.69591.788872001.8618
0.69381.838574001.8422
0.68471.888276001.8499
0.66011.937978001.8307
0.64231.987680001.8136
0.62752.037382001.8181
0.63612.087084001.8578
0.63232.136686001.8541
0.61922.186388001.8347
0.62732.236090001.8254
0.59392.285792001.8243
0.59942.335494001.8133
0.5912.385196001.8312
0.56192.434898001.8509
0.60132.4845100001.8538
0.55382.5342102001.8633
0.56232.5839104001.7793
0.58242.6335106001.8132
0.56112.6832108001.8083
0.54932.7329110001.8147
0.53292.7826112001.7890
0.53742.8323114001.7984
0.53892.8820116001.8228
0.51932.9317118001.7950
0.52222.9814120001.8798
0.5233.0311122001.8300
0.48893.0807124001.8481
0.51433.1304126001.8807
0.49613.1801128001.7871
0.49613.2298130001.8220
0.5033.2795132001.8354
0.49363.3292134001.8162
0.47533.3789136001.8069
0.49713.4286138001.8034
0.49013.4783140001.8229
0.49213.5280142001.8046
0.48733.5776144001.8074
0.46973.6273146001.7865
0.4783.6770148001.7935
0.46573.7267150001.8454
0.46163.7764152001.8294
0.44633.8261154001.8229
0.44893.8758156001.8061
0.46283.9255158001.8125
0.4243.9752160001.7936
0.45364.0248162001.8191
0.43474.0745164001.8064
0.43334.1242166001.8251
0.46114.1739168001.8013
0.43814.2236170001.8054
0.44914.2733172001.8044
0.42624.3230174001.8105
0.43564.3727176001.8472
0.43154.4224178001.8449
0.43644.4720180001.7980
0.41344.5217182001.8057
0.44174.5714184001.8060
0.40824.6211186001.8169
0.41554.6708188001.7955
0.41464.7205190001.7947
0.40114.7702192001.7869
0.41074.8199194001.8057
0.40994.8696196001.8007
0.41864.9193198001.7996
0.39434.9689200001.8203
0.40665.0186202001.8108
0.38995.0683204001.8313
0.4045.1180206001.8058
0.39465.1677208001.8053
0.40035.2174210001.8303
0.38655.2671212001.8430
0.39175.3168214001.8160
0.39525.3665216001.8379
0.39835.4161218001.8183
0.37045.4658220001.8574
0.39235.5155222001.8571
0.4045.5652224001.8146
0.38925.6149226001.8386
0.39235.6646228001.8043
0.38795.7143230001.8278
0.37685.7640232001.8183
0.38175.8137234001.8415
0.38175.8634236001.8258
0.39015.9130238001.8612
0.395.9627240001.7939
0.37046.0124242001.8254
0.37596.0621244001.8531
0.36426.1118246001.8282
0.36926.1615248001.8415
0.37556.2112250001.8282
0.37866.2609252001.8480
0.37526.3106254001.8108
0.35676.3602256001.8374
0.36856.4099258001.8302
0.36776.4596260001.8064
0.36086.5093262001.8223
0.37726.5590264001.8755
0.37786.6087266001.8252
0.37086.6584268001.8462
0.36296.7081270001.8216
0.37356.7578272001.8410
0.36276.8075274001.8334
0.3536.8571276001.8406
0.37116.9068278001.8674
0.35436.9565280001.8352
0.37097.0062282001.8477
0.35657.0559284001.8331
0.35497.1056286001.8234
0.36297.1553288001.8365
0.35417.2050290001.8365
0.34687.2547292001.8321
0.35277.3043294001.8489
0.36087.3540296001.8420
0.3657.4037298001.8372
0.36687.4534300001.8356
0.35537.5031302001.8418
0.34567.5528304001.8356
0.35787.6025306001.8243
0.3537.6522308001.8492
0.3427.7019310001.8441
0.34937.7516312001.8292
0.35537.8012314001.8441
0.35297.8509316001.8383
0.34027.9006318001.8447
0.35627.9503320001.8356
0.37358.0322001.8358

Framework versions

  • —PEFT 0.12.0
  • —Transformers 4.47.1
  • —Pytorch 2.5.1+cu124
  • —Datasets 3.2.0
  • —Tokenizers 0.21.0