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---
license: apache-2.0
base_model: agemagician/mlong-t5-tglobal-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mlong-t5-tglobal-base
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. -->
# mlong-t5-tglobal-base
This model is a fine-tuned version of [agemagician/mlong-t5-tglobal-base](https://huggingface.co/agemagician/mlong-t5-tglobal-base) on an HeSum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1091
- Rouge1: 31.6099
- Rouge2: 12.9182
- Rougel: 23.8053
- Rougelsum: 25.5362
- Gen Len: 59.758
## 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: 5e-05
- train_batch_size: 1
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | RougeL | RougeLSum |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| No log | 1.0 | 500 | 2.2709 | 20.5043 | 8.1518 | 16.9526 | 17.5001 |
| 2.8714 | 2.0 | 1000 | 2.2022 | 21.4051 | 8.7445 | 17.7534 | 18.3191 |
| 2.8714 | 3.0 | 1500 | 2.1608 | 21.6609 | 9.1753 | 18.0374 | 18.6176 |
| 2.5137 | 4.0 | 2000 | 2.1555 | 21.6818 | 9.1814 | 18.0382 | 18.6198 |
| 2.5137 | 5.0 | 2500 | 2.1462 | 21.9708 | 9.2033 | 18.3919 | 18.9535 |
| 2.3717 | 6.0 | 3000 | 2.1258 | 22.0583 | 9.2987 | 18.4379 | 19.0322 |
| 2.3717 | 7.0 | 3500 | 2.1278 | 21.8245 | 9.0474 | 18.1979 | 18.8038 |
| 2.2633 | 8.0 | 4000 | 2.1207 | 21.6273 | 8.8847 | 18.024 | 18.6049 |
| 2.2633 | 9.0 | 4500 | 2.1180 | 22.2004 | 9.6253 | 18.6373 | 19.1721 |
| 2.1886 | 10.0 | 5000 | 2.1220 | 22.1619 | 9.6206 | 18.5069 | 19.0856 |
| 2.1886 | 11.0 | 5500 | 2.1161 | 22.1518 | 9.4522 | 18.4695 | 19.0552 |
| 2.1144 | 12.0 | 6000 | 2.1103 | 22.0395 | 9.4185 | 18.4314 | 19.0305 |
| 2.1144 | 13.0 | 6500 | 2.1150 | 22.2404 | 9.4722 | 18.5482 | 19.1747 |
| 2.054 | 14.0 | 7000 | 2.1091 | 22.1466 | 9.3434 | 18.3443 | 18.9233 |
| 2.0526 | 15.0 | 8000 | 2.1580 | 30.4149 | 2.0774 | 22.9493 | 24.4478 |
| 2.1236 | 16.0 | 16000 | 2.1621 | 31.3101 | 13.3237 | 23.8249 | 25.526 |
| 2.0776 | 17.0 | 24000 | 2.1607 | 30.9902 | 12.3753 | 23.0243 | 24.8308 |
| 1.9843 | 18.0 | 32000 | 2.1553 | 32.0603 | 13.4985 | 24.0775 | 25.9692 |
### Framework versions
- Transformers 4.38.2
- Pytorch 1.13.1+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2 |