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---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: synthea_t5_summarization_model
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# synthea_t5_summarization_model
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2906
- Rouge1: 0.4543
- Rouge2: 0.137
- Rougel: 0.4022
- Rougelsum: 0.4025
- Gen Len: 11.1279
## 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: 40
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log | 1.0 | 22 | 1.9114 | 0.289 | 0.0651 | 0.2709 | 0.2713 | 9.6279 |
| No log | 2.0 | 44 | 1.8289 | 0.3265 | 0.0822 | 0.2925 | 0.2935 | 10.2093 |
| No log | 3.0 | 66 | 1.7603 | 0.3617 | 0.107 | 0.3224 | 0.323 | 10.9651 |
| No log | 4.0 | 88 | 1.7081 | 0.3505 | 0.1017 | 0.3142 | 0.3146 | 11.7674 |
| No log | 5.0 | 110 | 1.6651 | 0.3497 | 0.0935 | 0.3055 | 0.3066 | 11.9419 |
| No log | 6.0 | 132 | 1.6200 | 0.3701 | 0.1022 | 0.3339 | 0.3348 | 11.7209 |
| No log | 7.0 | 154 | 1.5865 | 0.3726 | 0.1045 | 0.3328 | 0.3336 | 11.6279 |
| No log | 8.0 | 176 | 1.5552 | 0.3802 | 0.1049 | 0.3412 | 0.3417 | 11.4419 |
| No log | 9.0 | 198 | 1.5237 | 0.3982 | 0.115 | 0.3519 | 0.3533 | 11.3721 |
| No log | 10.0 | 220 | 1.4836 | 0.41 | 0.1188 | 0.3643 | 0.3645 | 11.4767 |
| No log | 11.0 | 242 | 1.4708 | 0.391 | 0.1142 | 0.3492 | 0.3491 | 11.6977 |
| No log | 12.0 | 264 | 1.4429 | 0.4157 | 0.1184 | 0.3689 | 0.3687 | 11.1977 |
| No log | 13.0 | 286 | 1.4312 | 0.4229 | 0.1204 | 0.3738 | 0.3741 | 11.0698 |
| No log | 14.0 | 308 | 1.4162 | 0.4231 | 0.1361 | 0.3806 | 0.3805 | 11.0465 |
| No log | 15.0 | 330 | 1.4011 | 0.4341 | 0.1406 | 0.3856 | 0.386 | 10.8953 |
| No log | 16.0 | 352 | 1.3877 | 0.439 | 0.1373 | 0.3942 | 0.3952 | 11.407 |
| No log | 17.0 | 374 | 1.3794 | 0.4488 | 0.1442 | 0.3987 | 0.3997 | 11.0581 |
| No log | 18.0 | 396 | 1.3673 | 0.4445 | 0.1418 | 0.3972 | 0.3979 | 11.186 |
| No log | 19.0 | 418 | 1.3581 | 0.4529 | 0.1375 | 0.4037 | 0.4047 | 11.1279 |
| No log | 20.0 | 440 | 1.3515 | 0.4378 | 0.1216 | 0.3921 | 0.3921 | 11.0 |
| No log | 21.0 | 462 | 1.3430 | 0.4533 | 0.1344 | 0.3996 | 0.4012 | 10.6512 |
| No log | 22.0 | 484 | 1.3390 | 0.4489 | 0.1426 | 0.4041 | 0.4042 | 10.8023 |
| 1.8003 | 23.0 | 506 | 1.3341 | 0.4444 | 0.1359 | 0.3986 | 0.3992 | 10.7674 |
| 1.8003 | 24.0 | 528 | 1.3266 | 0.4525 | 0.1357 | 0.4058 | 0.4059 | 10.9186 |
| 1.8003 | 25.0 | 550 | 1.3290 | 0.4517 | 0.1304 | 0.4024 | 0.4027 | 10.7209 |
| 1.8003 | 26.0 | 572 | 1.3217 | 0.4486 | 0.1405 | 0.402 | 0.402 | 11.4186 |
| 1.8003 | 27.0 | 594 | 1.3194 | 0.4484 | 0.1383 | 0.4004 | 0.401 | 11.1279 |
| 1.8003 | 28.0 | 616 | 1.3158 | 0.4407 | 0.1284 | 0.3946 | 0.395 | 11.4302 |
| 1.8003 | 29.0 | 638 | 1.3111 | 0.4457 | 0.1294 | 0.3974 | 0.397 | 11.2558 |
| 1.8003 | 30.0 | 660 | 1.3075 | 0.4502 | 0.132 | 0.3988 | 0.398 | 11.0581 |
| 1.8003 | 31.0 | 682 | 1.3045 | 0.4482 | 0.1328 | 0.3965 | 0.3963 | 11.0698 |
| 1.8003 | 32.0 | 704 | 1.3012 | 0.4492 | 0.1315 | 0.3978 | 0.3971 | 11.093 |
| 1.8003 | 33.0 | 726 | 1.2988 | 0.4426 | 0.1294 | 0.3922 | 0.3923 | 11.2326 |
| 1.8003 | 34.0 | 748 | 1.2978 | 0.451 | 0.1342 | 0.3992 | 0.3998 | 11.1512 |
| 1.8003 | 35.0 | 770 | 1.2980 | 0.4556 | 0.1386 | 0.4062 | 0.4069 | 11.0698 |
| 1.8003 | 36.0 | 792 | 1.2946 | 0.4578 | 0.1387 | 0.4063 | 0.4062 | 11.0581 |
| 1.8003 | 37.0 | 814 | 1.2921 | 0.4549 | 0.138 | 0.4031 | 0.4031 | 11.1047 |
| 1.8003 | 38.0 | 836 | 1.2910 | 0.4531 | 0.1362 | 0.4014 | 0.4017 | 11.1512 |
| 1.8003 | 39.0 | 858 | 1.2907 | 0.4531 | 0.1362 | 0.4014 | 0.4017 | 11.0814 |
| 1.8003 | 40.0 | 880 | 1.2906 | 0.4543 | 0.137 | 0.4022 | 0.4025 | 11.1279 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2
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