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bart-large-cnn-finetuned-prompt_generation

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metadata
license: mit
base_model: facebook/bart-large-cnn
tags:
  - generated_from_trainer
model-index:
  - name: bart-large-cnn-finetuned-prompt_generation
    results: []

bart-large-cnn-finetuned-prompt_generation

This model is a fine-tuned version of facebook/bart-large-cnn on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 2.8294
  • Map: 0.4211
  • Ndcg@10: 0.6088

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: 3e-07
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 100

Training results

Training Loss Epoch Step Validation Loss Map Ndcg@10
No log 1.0 2 3.6607 0.3400 0.4882
No log 2.0 4 3.6575 0.3 0.4282
No log 3.0 6 3.6485 0.3183 0.5016
No log 4.0 8 3.6279 0.3183 0.4899
No log 5.0 10 3.6199 0.3183 0.4899
No log 6.0 12 3.6119 0.3123 0.5016
No log 7.0 14 3.6076 0.3323 0.5299
No log 8.0 16 3.5413 0.3523 0.5733
No log 9.0 18 3.5274 0.345 0.5333
No log 10.0 20 3.5184 0.3200 0.4816
No log 11.0 22 3.5041 0.3200 0.5016
No log 12.0 24 3.4935 0.3133 0.4899
No log 13.0 26 3.4858 0.31 0.4951
No log 14.0 28 3.4763 0.31 0.5068
No log 15.0 30 3.3761 0.34 0.5434
No log 16.0 32 3.3314 0.345 0.5751
No log 17.0 34 3.3103 0.3283 0.5468
No log 18.0 36 3.2951 0.3233 0.5151
No log 19.0 38 3.2811 0.3233 0.5034
No log 20.0 40 3.2708 0.3167 0.4834
No log 21.0 42 3.2625 0.3233 0.4834
No log 22.0 44 3.2471 0.3133 0.4834
No log 23.0 46 3.2308 0.3067 0.5034
No log 24.0 48 3.2171 0.2867 0.4634
No log 25.0 50 3.2068 0.2933 0.4751
No log 26.0 52 3.1972 0.2890 0.4803
No log 27.0 54 3.1892 0.2757 0.4252
No log 28.0 56 3.1812 0.2823 0.4252
No log 29.0 58 3.1681 0.309 0.4769
No log 30.0 60 3.1422 0.3223 0.4969
No log 31.0 62 3.1154 0.309 0.4769
No log 32.0 64 3.0906 0.369 0.5539
No log 33.0 66 3.0680 0.3850 0.5486
No log 34.0 68 3.0476 0.3567 0.5139
No log 35.0 70 3.0301 0.3347 0.4909
No log 36.0 72 3.0159 0.2861 0.4581
No log 37.0 74 3.0040 0.2887 0.4678
No log 38.0 76 2.9937 0.3003 0.4374
No log 39.0 78 2.9842 0.2723 0.3950
No log 40.0 80 2.9759 0.3052 0.4695
No log 41.0 82 2.9686 0.2867 0.4459
No log 42.0 84 2.9622 0.3099 0.4764
No log 43.0 86 2.9565 0.3141 0.5019
No log 44.0 88 2.9512 0.325 0.5204
No log 45.0 90 2.9462 0.3050 0.5004
No log 46.0 92 2.9416 0.325 0.5151
No log 47.0 94 2.9372 0.3183 0.4951
No log 48.0 96 2.9325 0.318 0.5235
No log 49.0 98 2.9278 0.318 0.5269
No log 50.0 100 2.9228 0.3155 0.5380
No log 51.0 102 2.9178 0.2795 0.4823
No log 52.0 104 2.9127 0.3329 0.5655
No log 53.0 106 2.9081 0.3127 0.5455
No log 54.0 108 2.9037 0.3195 0.5642
No log 55.0 110 2.8995 0.3145 0.5442
No log 56.0 112 2.8957 0.3245 0.5759
No log 57.0 114 2.8922 0.3798 0.6383
No log 58.0 116 2.8886 0.3788 0.6405
No log 59.0 118 2.8854 0.3920 0.6502
No log 60.0 120 2.8822 0.3920 0.6376
No log 61.0 122 2.8793 0.4255 0.6796
No log 62.0 124 2.8766 0.4288 0.7089
No log 63.0 126 2.8738 0.4340 0.7048
No log 64.0 128 2.8712 0.4273 0.6889
No log 65.0 130 2.8688 0.4173 0.7067
No log 66.0 132 2.8665 0.4233 0.6802
No log 67.0 134 2.8642 0.3973 0.6309
No log 68.0 136 2.8620 0.4107 0.6574
No log 69.0 138 2.8599 0.4173 0.6774
No log 70.0 140 2.8580 0.3907 0.6109
No log 71.0 142 2.8560 0.4407 0.6596
No log 72.0 144 2.8542 0.4007 0.6196
No log 73.0 146 2.8525 0.4207 0.6396
No log 74.0 148 2.8508 0.4173 0.6596
No log 75.0 150 2.8491 0.4107 0.6303
No log 76.0 152 2.8476 0.3973 0.5986
No log 77.0 154 2.8460 0.4040 0.6186
No log 78.0 156 2.8447 0.414 0.6747
No log 79.0 158 2.8433 0.4167 0.6673
No log 80.0 160 2.8420 0.4457 0.6813
No log 81.0 162 2.8409 0.4257 0.6512
No log 82.0 164 2.8397 0.4607 0.7073
No log 83.0 166 2.8387 0.4257 0.6048
No log 84.0 168 2.8377 0.4207 0.6048
No log 85.0 170 2.8366 0.369 0.5248
No log 86.0 172 2.8357 0.4111 0.5971
No log 87.0 174 2.8350 0.389 0.5448
No log 88.0 176 2.8342 0.4028 0.5771
No log 89.0 178 2.8334 0.374 0.5448
No log 90.0 180 2.8328 0.374 0.5565
No log 91.0 182 2.8321 0.4078 0.5971
No log 92.0 184 2.8316 0.4011 0.5888
No log 93.0 186 2.8311 0.374 0.5565
No log 94.0 188 2.8308 0.3811 0.5688
No log 95.0 190 2.8304 0.374 0.5565
No log 96.0 192 2.8302 0.3911 0.5888
No log 97.0 194 2.8300 0.3611 0.5488
No log 98.0 196 2.8297 0.414 0.5848
No log 99.0 198 2.8295 0.3878 0.5888
No log 100.0 200 2.8294 0.4211 0.6088

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1