metadata
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: genz_model
results: []
genz_model
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2536
- Bleu: 40.0734
- Gen Len: 15.8667
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: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| No log | 1.0 | 41 | 1.9667 | 16.4087 | 16.3333 |
| No log | 2.0 | 82 | 1.8242 | 30.3437 | 15.4788 |
| No log | 3.0 | 123 | 1.7376 | 35.0542 | 15.6545 |
| No log | 4.0 | 164 | 1.6830 | 36.3815 | 15.9091 |
| No log | 5.0 | 205 | 1.6438 | 37.3325 | 15.9212 |
| No log | 6.0 | 246 | 1.6052 | 37.5162 | 16.0364 |
| No log | 7.0 | 287 | 1.5723 | 37.5334 | 16.097 |
| No log | 8.0 | 328 | 1.5484 | 38.2319 | 16.1152 |
| No log | 9.0 | 369 | 1.5249 | 38.3884 | 16.1455 |
| No log | 10.0 | 410 | 1.5040 | 38.4443 | 16.1394 |
| No log | 11.0 | 451 | 1.4852 | 38.8279 | 16.1879 |
| No log | 12.0 | 492 | 1.4706 | 39.4717 | 16.0424 |
| 1.7321 | 13.0 | 533 | 1.4525 | 39.6365 | 16.103 |
| 1.7321 | 14.0 | 574 | 1.4361 | 39.7667 | 16.0545 |
| 1.7321 | 15.0 | 615 | 1.4237 | 39.934 | 16.0182 |
| 1.7321 | 16.0 | 656 | 1.4084 | 39.8808 | 16.0606 |
| 1.7321 | 17.0 | 697 | 1.4013 | 39.958 | 16.0606 |
| 1.7321 | 18.0 | 738 | 1.3875 | 39.4972 | 16.0788 |
| 1.7321 | 19.0 | 779 | 1.3770 | 39.4976 | 15.9394 |
| 1.7321 | 20.0 | 820 | 1.3681 | 39.4927 | 15.9818 |
| 1.7321 | 21.0 | 861 | 1.3592 | 39.8584 | 15.9818 |
| 1.7321 | 22.0 | 902 | 1.3512 | 39.9409 | 15.9515 |
| 1.7321 | 23.0 | 943 | 1.3414 | 39.8891 | 15.9576 |
| 1.7321 | 24.0 | 984 | 1.3367 | 40.0053 | 15.9576 |
| 1.3831 | 25.0 | 1025 | 1.3298 | 39.9729 | 15.9636 |
| 1.3831 | 26.0 | 1066 | 1.3231 | 40.0029 | 15.9333 |
| 1.3831 | 27.0 | 1107 | 1.3157 | 39.9874 | 15.9394 |
| 1.3831 | 28.0 | 1148 | 1.3093 | 39.8156 | 15.9152 |
| 1.3831 | 29.0 | 1189 | 1.3051 | 40.1371 | 15.9152 |
| 1.3831 | 30.0 | 1230 | 1.3006 | 40.0601 | 15.897 |
| 1.3831 | 31.0 | 1271 | 1.2950 | 40.2356 | 15.8727 |
| 1.3831 | 32.0 | 1312 | 1.2899 | 40.3369 | 15.8848 |
| 1.3831 | 33.0 | 1353 | 1.2871 | 40.452 | 15.8667 |
| 1.3831 | 34.0 | 1394 | 1.2836 | 40.5232 | 15.8364 |
| 1.3831 | 35.0 | 1435 | 1.2804 | 40.455 | 15.8485 |
| 1.3831 | 36.0 | 1476 | 1.2768 | 40.4874 | 15.8485 |
| 1.2414 | 37.0 | 1517 | 1.2728 | 40.5694 | 15.8424 |
| 1.2414 | 38.0 | 1558 | 1.2692 | 40.4767 | 15.8424 |
| 1.2414 | 39.0 | 1599 | 1.2679 | 40.5449 | 15.8424 |
| 1.2414 | 40.0 | 1640 | 1.2650 | 40.5121 | 15.8667 |
| 1.2414 | 41.0 | 1681 | 1.2625 | 40.0705 | 15.8545 |
| 1.2414 | 42.0 | 1722 | 1.2604 | 40.056 | 15.8545 |
| 1.2414 | 43.0 | 1763 | 1.2597 | 40.1238 | 15.8667 |
| 1.2414 | 44.0 | 1804 | 1.2579 | 40.0473 | 15.8606 |
| 1.2414 | 45.0 | 1845 | 1.2565 | 40.0792 | 15.8667 |
| 1.2414 | 46.0 | 1886 | 1.2553 | 40.0734 | 15.8667 |
| 1.2414 | 47.0 | 1927 | 1.2545 | 40.0734 | 15.8667 |
| 1.2414 | 48.0 | 1968 | 1.2539 | 40.0734 | 15.8667 |
| 1.179 | 49.0 | 2009 | 1.2537 | 40.0734 | 15.8667 |
| 1.179 | 50.0 | 2050 | 1.2536 | 40.0734 | 15.8667 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.2
- Tokenizers 0.13.3