my_awesome_billsum_model_48
This model is a fine-tuned version of google-t5/t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2139
- Rouge1: 0.9715
- Rouge2: 0.8711
- Rougel: 0.9127
- Rougelsum: 0.9125
- Gen Len: 5.3542
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: 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
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
No log | 1.0 | 12 | 1.8158 | 0.4272 | 0.3079 | 0.4 | 0.4005 | 17.3125 |
No log | 2.0 | 24 | 1.2144 | 0.4698 | 0.3444 | 0.4393 | 0.4402 | 15.75 |
No log | 3.0 | 36 | 0.7083 | 0.8027 | 0.7117 | 0.7672 | 0.7688 | 8.6875 |
No log | 4.0 | 48 | 0.5359 | 0.9573 | 0.8615 | 0.905 | 0.9067 | 5.4375 |
No log | 5.0 | 60 | 0.4880 | 0.9573 | 0.8615 | 0.905 | 0.9067 | 5.4375 |
No log | 6.0 | 72 | 0.4493 | 0.9635 | 0.8621 | 0.8952 | 0.8965 | 5.1875 |
No log | 7.0 | 84 | 0.4190 | 0.9596 | 0.8438 | 0.8771 | 0.8758 | 5.2292 |
No log | 8.0 | 96 | 0.4026 | 0.9636 | 0.8666 | 0.8941 | 0.8923 | 5.2917 |
No log | 9.0 | 108 | 0.3907 | 0.9663 | 0.877 | 0.9025 | 0.9012 | 5.3125 |
No log | 10.0 | 120 | 0.3805 | 0.9639 | 0.8681 | 0.895 | 0.8947 | 5.3333 |
No log | 11.0 | 132 | 0.3761 | 0.9639 | 0.8681 | 0.895 | 0.8947 | 5.3333 |
No log | 12.0 | 144 | 0.3686 | 0.9639 | 0.8681 | 0.895 | 0.8947 | 5.3333 |
No log | 13.0 | 156 | 0.3611 | 0.9639 | 0.8681 | 0.895 | 0.8947 | 5.3333 |
No log | 14.0 | 168 | 0.3529 | 0.9639 | 0.8681 | 0.895 | 0.8947 | 5.3333 |
No log | 15.0 | 180 | 0.3467 | 0.9639 | 0.8681 | 0.895 | 0.8947 | 5.3333 |
No log | 16.0 | 192 | 0.3374 | 0.9639 | 0.8681 | 0.895 | 0.8947 | 5.3333 |
No log | 17.0 | 204 | 0.3272 | 0.9639 | 0.8681 | 0.895 | 0.8947 | 5.3333 |
No log | 18.0 | 216 | 0.3210 | 0.9663 | 0.877 | 0.9025 | 0.9012 | 5.3125 |
No log | 19.0 | 228 | 0.3186 | 0.9663 | 0.877 | 0.9025 | 0.9012 | 5.3125 |
No log | 20.0 | 240 | 0.3141 | 0.9663 | 0.877 | 0.9025 | 0.9012 | 5.3125 |
No log | 21.0 | 252 | 0.3092 | 0.9639 | 0.8681 | 0.895 | 0.8947 | 5.3333 |
No log | 22.0 | 264 | 0.3050 | 0.9669 | 0.8753 | 0.9038 | 0.9036 | 5.3542 |
No log | 23.0 | 276 | 0.3048 | 0.9669 | 0.8753 | 0.9038 | 0.9036 | 5.3542 |
No log | 24.0 | 288 | 0.2992 | 0.9663 | 0.8773 | 0.9061 | 0.9068 | 5.3125 |
No log | 25.0 | 300 | 0.2951 | 0.9639 | 0.8578 | 0.8976 | 0.8968 | 5.3333 |
No log | 26.0 | 312 | 0.2915 | 0.9639 | 0.8578 | 0.8976 | 0.8968 | 5.3333 |
No log | 27.0 | 324 | 0.2861 | 0.9639 | 0.8578 | 0.8976 | 0.8968 | 5.3333 |
No log | 28.0 | 336 | 0.2855 | 0.9691 | 0.8724 | 0.9149 | 0.9136 | 5.3333 |
No log | 29.0 | 348 | 0.2856 | 0.9691 | 0.8724 | 0.9149 | 0.9136 | 5.3333 |
No log | 30.0 | 360 | 0.2845 | 0.9691 | 0.8724 | 0.9149 | 0.9136 | 5.3333 |
No log | 31.0 | 372 | 0.2801 | 0.9691 | 0.8724 | 0.9149 | 0.9136 | 5.3333 |
No log | 32.0 | 384 | 0.2753 | 0.9664 | 0.8643 | 0.9073 | 0.9065 | 5.3542 |
No log | 33.0 | 396 | 0.2724 | 0.9664 | 0.8643 | 0.9073 | 0.9065 | 5.3542 |
No log | 34.0 | 408 | 0.2684 | 0.9691 | 0.8724 | 0.9149 | 0.9136 | 5.3333 |
No log | 35.0 | 420 | 0.2627 | 0.9691 | 0.8724 | 0.9149 | 0.9136 | 5.3333 |
No log | 36.0 | 432 | 0.2569 | 0.9685 | 0.8647 | 0.9029 | 0.9027 | 5.3333 |
No log | 37.0 | 444 | 0.2544 | 0.9685 | 0.8647 | 0.9029 | 0.9027 | 5.3333 |
No log | 38.0 | 456 | 0.2524 | 0.9695 | 0.8633 | 0.9057 | 0.905 | 5.375 |
No log | 39.0 | 468 | 0.2511 | 0.9695 | 0.8633 | 0.9057 | 0.905 | 5.375 |
No log | 40.0 | 480 | 0.2506 | 0.9695 | 0.8633 | 0.9057 | 0.905 | 5.375 |
No log | 41.0 | 492 | 0.2487 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.4449 | 42.0 | 504 | 0.2498 | 0.9695 | 0.8633 | 0.9057 | 0.905 | 5.375 |
0.4449 | 43.0 | 516 | 0.2520 | 0.9695 | 0.8633 | 0.9057 | 0.905 | 5.375 |
0.4449 | 44.0 | 528 | 0.2505 | 0.9721 | 0.8823 | 0.9144 | 0.9151 | 5.3542 |
0.4449 | 45.0 | 540 | 0.2483 | 0.9721 | 0.8823 | 0.9144 | 0.9151 | 5.3542 |
0.4449 | 46.0 | 552 | 0.2475 | 0.9695 | 0.8633 | 0.9057 | 0.905 | 5.375 |
0.4449 | 47.0 | 564 | 0.2491 | 0.9695 | 0.8633 | 0.9057 | 0.905 | 5.375 |
0.4449 | 48.0 | 576 | 0.2524 | 0.9695 | 0.8633 | 0.9057 | 0.905 | 5.375 |
0.4449 | 49.0 | 588 | 0.2523 | 0.9695 | 0.8633 | 0.9057 | 0.905 | 5.375 |
0.4449 | 50.0 | 600 | 0.2496 | 0.9695 | 0.8633 | 0.9057 | 0.905 | 5.375 |
0.4449 | 51.0 | 612 | 0.2487 | 0.9695 | 0.8633 | 0.9057 | 0.905 | 5.375 |
0.4449 | 52.0 | 624 | 0.2475 | 0.9695 | 0.8633 | 0.9057 | 0.905 | 5.375 |
0.4449 | 53.0 | 636 | 0.2472 | 0.9695 | 0.8633 | 0.9057 | 0.905 | 5.375 |
0.4449 | 54.0 | 648 | 0.2426 | 0.9695 | 0.8633 | 0.9057 | 0.905 | 5.375 |
0.4449 | 55.0 | 660 | 0.2407 | 0.9695 | 0.8633 | 0.9057 | 0.905 | 5.375 |
0.4449 | 56.0 | 672 | 0.2422 | 0.9695 | 0.8633 | 0.9057 | 0.905 | 5.375 |
0.4449 | 57.0 | 684 | 0.2431 | 0.9695 | 0.8633 | 0.9057 | 0.905 | 5.375 |
0.4449 | 58.0 | 696 | 0.2388 | 0.9695 | 0.8633 | 0.9057 | 0.905 | 5.375 |
0.4449 | 59.0 | 708 | 0.2372 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.4449 | 60.0 | 720 | 0.2340 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.4449 | 61.0 | 732 | 0.2326 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.4449 | 62.0 | 744 | 0.2330 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.4449 | 63.0 | 756 | 0.2342 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.4449 | 64.0 | 768 | 0.2328 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.4449 | 65.0 | 780 | 0.2329 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.4449 | 66.0 | 792 | 0.2298 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.4449 | 67.0 | 804 | 0.2281 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.4449 | 68.0 | 816 | 0.2272 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.4449 | 69.0 | 828 | 0.2266 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.4449 | 70.0 | 840 | 0.2256 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.4449 | 71.0 | 852 | 0.2234 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.4449 | 72.0 | 864 | 0.2219 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.4449 | 73.0 | 876 | 0.2235 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.4449 | 74.0 | 888 | 0.2236 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.4449 | 75.0 | 900 | 0.2220 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.4449 | 76.0 | 912 | 0.2201 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.4449 | 77.0 | 924 | 0.2218 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.4449 | 78.0 | 936 | 0.2220 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.4449 | 79.0 | 948 | 0.2215 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.4449 | 80.0 | 960 | 0.2219 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.4449 | 81.0 | 972 | 0.2210 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.4449 | 82.0 | 984 | 0.2200 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.4449 | 83.0 | 996 | 0.2199 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.1072 | 84.0 | 1008 | 0.2186 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.1072 | 85.0 | 1020 | 0.2184 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.1072 | 86.0 | 1032 | 0.2181 | 0.9715 | 0.8848 | 0.9179 | 0.9177 | 5.3542 |
0.1072 | 87.0 | 1044 | 0.2162 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.1072 | 88.0 | 1056 | 0.2161 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.1072 | 89.0 | 1068 | 0.2157 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.1072 | 90.0 | 1080 | 0.2156 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.1072 | 91.0 | 1092 | 0.2149 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.1072 | 92.0 | 1104 | 0.2145 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.1072 | 93.0 | 1116 | 0.2146 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.1072 | 94.0 | 1128 | 0.2146 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.1072 | 95.0 | 1140 | 0.2145 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.1072 | 96.0 | 1152 | 0.2141 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.1072 | 97.0 | 1164 | 0.2141 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.1072 | 98.0 | 1176 | 0.2140 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.1072 | 99.0 | 1188 | 0.2139 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
0.1072 | 100.0 | 1200 | 0.2139 | 0.9715 | 0.8711 | 0.9127 | 0.9125 | 5.3542 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Downloads last month
- 3
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for limaatulya/my_awesome_billsum_model_48
Base model
google-t5/t5-small