metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: output
results: []
output
This model is a fine-tuned version of google/flan-t5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1885
- Rouge1: 65.4762
- Rouge2: 0.0
- Rougel: 65.4762
- Rougelsum: 65.4762
- Gen Len: 2.1905
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-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
- lr_scheduler_warmup_steps: 20
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 1.2679 | 1.0 | 42 | 1.3033 | 48.8095 | 0.0 | 48.8095 | 48.8095 | 4.0119 |
| 1.0917 | 2.0 | 84 | 1.1075 | 48.8095 | 0.0 | 48.8095 | 48.8095 | 2.2738 |
| 0.8305 | 3.0 | 126 | 1.0366 | 45.2381 | 0.0 | 45.2381 | 45.2381 | 2.3095 |
| 0.6058 | 4.0 | 168 | 0.9865 | 48.8095 | 0.0 | 48.8095 | 48.8095 | 2.4524 |
| 0.5114 | 5.0 | 210 | 0.9289 | 55.9524 | 0.0 | 55.9524 | 55.9524 | 2.4048 |
| 0.6026 | 6.0 | 252 | 0.9373 | 53.5714 | 0.0 | 53.5714 | 53.5714 | 2.3214 |
| 0.6428 | 7.0 | 294 | 0.8762 | 53.5714 | 0.0 | 53.5714 | 53.5714 | 2.3095 |
| 0.5375 | 8.0 | 336 | 0.8908 | 54.7619 | 0.0 | 54.7619 | 54.7619 | 2.3333 |
| 0.4296 | 9.0 | 378 | 0.9172 | 50.0 | 0.0 | 50.0 | 50.0 | 2.3452 |
| 0.4644 | 10.0 | 420 | 0.8882 | 60.7143 | 0.0 | 60.7143 | 60.7143 | 2.3452 |
| 0.42 | 11.0 | 462 | 0.8917 | 54.7619 | 0.0 | 54.7619 | 54.7619 | 2.2619 |
| 0.3727 | 12.0 | 504 | 0.8710 | 55.9524 | 0.0 | 55.9524 | 55.9524 | 2.3571 |
| 0.4061 | 13.0 | 546 | 0.8817 | 54.7619 | 0.0 | 54.7619 | 54.7619 | 2.2857 |
| 0.3221 | 14.0 | 588 | 0.9284 | 57.1429 | 0.0 | 57.1429 | 57.1429 | 2.2857 |
| 0.3676 | 15.0 | 630 | 0.9313 | 57.1429 | 0.0 | 57.1429 | 57.1429 | 2.0476 |
| 0.264 | 16.0 | 672 | 0.9315 | 59.5238 | 0.0 | 59.5238 | 59.5238 | 2.0595 |
| 0.2933 | 17.0 | 714 | 0.9265 | 64.2857 | 0.0 | 64.2857 | 64.2857 | 2.1310 |
| 0.2446 | 18.0 | 756 | 0.9254 | 61.9048 | 0.0 | 61.9048 | 61.9048 | 2.0714 |
| 0.2356 | 19.0 | 798 | 0.9390 | 63.0952 | 0.0 | 63.0952 | 63.0952 | 2.0714 |
| 0.3102 | 20.0 | 840 | 0.9837 | 61.9048 | 0.0 | 61.9048 | 61.9048 | 2.1071 |
| 0.1539 | 21.0 | 882 | 0.9727 | 60.7143 | 0.0 | 60.7143 | 60.7143 | 2.0952 |
| 0.1674 | 22.0 | 924 | 1.0114 | 61.9048 | 0.0 | 61.9048 | 61.9048 | 2.0952 |
| 0.1831 | 23.0 | 966 | 0.9869 | 61.9048 | 0.0 | 61.9048 | 61.9048 | 2.0595 |
| 0.201 | 24.0 | 1008 | 0.9904 | 60.7143 | 0.0 | 60.7143 | 60.7143 | 2.0595 |
| 0.1602 | 25.0 | 1050 | 0.9883 | 60.7143 | 0.0 | 60.7143 | 60.7143 | 2.0595 |
| 0.158 | 26.0 | 1092 | 1.0057 | 63.0952 | 0.0 | 63.0952 | 63.0952 | 2.1071 |
| 0.1468 | 27.0 | 1134 | 0.9998 | 67.8571 | 0.0 | 67.8571 | 67.8571 | 2.1429 |
| 0.109 | 28.0 | 1176 | 1.0052 | 63.0952 | 0.0 | 63.0952 | 63.0952 | 2.3333 |
| 0.1397 | 29.0 | 1218 | 1.0137 | 65.4762 | 0.0 | 65.4762 | 65.4762 | 2.3333 |
| 0.1204 | 30.0 | 1260 | 1.0482 | 63.0952 | 0.0 | 63.0952 | 63.0952 | 2.3452 |
| 0.1577 | 31.0 | 1302 | 1.0787 | 66.6667 | 0.0 | 66.6667 | 66.6667 | 2.3452 |
| 0.1112 | 32.0 | 1344 | 1.0513 | 63.0952 | 0.0 | 63.0952 | 63.0952 | 2.3452 |
| 0.0932 | 33.0 | 1386 | 1.0786 | 63.0952 | 0.0 | 63.0952 | 63.0952 | 2.3452 |
| 0.0989 | 34.0 | 1428 | 1.1378 | 63.0952 | 0.0 | 63.0952 | 63.0952 | 2.3452 |
| 0.0858 | 35.0 | 1470 | 1.1055 | 65.4762 | 0.0 | 65.4762 | 65.4762 | 2.3452 |
| 0.1056 | 36.0 | 1512 | 1.1297 | 64.2857 | 0.0 | 64.2857 | 64.2857 | 2.3571 |
| 0.14 | 37.0 | 1554 | 1.1604 | 64.2857 | 0.0 | 64.2857 | 64.2857 | 2.3452 |
| 0.0592 | 38.0 | 1596 | 1.1213 | 65.4762 | 0.0 | 65.4762 | 65.4762 | 2.3452 |
| 0.1121 | 39.0 | 1638 | 1.1489 | 65.4762 | 0.0 | 65.4762 | 65.4762 | 2.3452 |
| 0.1917 | 40.0 | 1680 | 1.1544 | 64.2857 | 0.0 | 64.2857 | 64.2857 | 2.3452 |
| 0.1178 | 41.0 | 1722 | 1.1561 | 64.2857 | 0.0 | 64.2857 | 64.2857 | 2.3452 |
| 0.0761 | 42.0 | 1764 | 1.2013 | 63.0952 | 0.0 | 63.0952 | 63.0952 | 2.1905 |
| 0.0911 | 43.0 | 1806 | 1.2075 | 64.2857 | 0.0 | 64.2857 | 64.2857 | 2.1548 |
| 0.1081 | 44.0 | 1848 | 1.2134 | 66.6667 | 0.0 | 66.6667 | 66.6667 | 2.1548 |
| 0.089 | 45.0 | 1890 | 1.1861 | 64.2857 | 0.0 | 64.2857 | 64.2857 | 2.1905 |
| 0.0828 | 46.0 | 1932 | 1.1988 | 65.4762 | 0.0 | 65.4762 | 65.4762 | 2.1905 |
| 0.0818 | 47.0 | 1974 | 1.1886 | 64.2857 | 0.0 | 64.2857 | 64.2857 | 2.1905 |
| 0.0899 | 48.0 | 2016 | 1.1988 | 64.2857 | 0.0 | 64.2857 | 64.2857 | 2.1905 |
| 0.0923 | 49.0 | 2058 | 1.1968 | 65.4762 | 0.0 | 65.4762 | 65.4762 | 2.1905 |
| 0.0859 | 50.0 | 2100 | 1.1885 | 65.4762 | 0.0 | 65.4762 | 65.4762 | 2.1905 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2