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---
license: apache-2.0
base_model: RMWeerasinghe/long-t5-tglobal-base-finetuned-govReport-4096
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: long-t5-tglobal-base-boardpapers-4096
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. -->
# long-t5-tglobal-base-boardpapers-4096
This model is a fine-tuned version of [RMWeerasinghe/long-t5-tglobal-base-finetuned-govReport-4096](https://huggingface.co/RMWeerasinghe/long-t5-tglobal-base-finetuned-govReport-4096) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5617
- Rouge1: 0.0743
- Rouge2: 0.0398
- Rougel: 0.0589
- Rougelsum: 0.0703
## 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: 4e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- 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 | 0.67 | 1 | 0.6654 | 0.0514 | 0.0197 | 0.0386 | 0.0477 |
| No log | 2.0 | 3 | 0.6378 | 0.0667 | 0.0309 | 0.0512 | 0.0596 |
| No log | 2.67 | 4 | 0.6293 | 0.0646 | 0.0274 | 0.0515 | 0.0619 |
| No log | 4.0 | 6 | 0.6128 | 0.0706 | 0.0377 | 0.0566 | 0.067 |
| No log | 4.67 | 7 | 0.6049 | 0.0706 | 0.0377 | 0.0566 | 0.067 |
| No log | 6.0 | 9 | 0.5935 | 0.0706 | 0.0377 | 0.0566 | 0.067 |
| No log | 6.67 | 10 | 0.5891 | 0.0718 | 0.0385 | 0.0578 | 0.067 |
| No log | 8.0 | 12 | 0.5815 | 0.0743 | 0.0398 | 0.0589 | 0.0703 |
| No log | 8.67 | 13 | 0.5785 | 0.0743 | 0.0398 | 0.0589 | 0.0703 |
| No log | 10.0 | 15 | 0.5742 | 0.0743 | 0.0398 | 0.0589 | 0.0703 |
| No log | 10.67 | 16 | 0.5724 | 0.0743 | 0.0398 | 0.0589 | 0.0703 |
| No log | 12.0 | 18 | 0.5694 | 0.0743 | 0.0398 | 0.0589 | 0.0703 |
| No log | 12.67 | 19 | 0.5681 | 0.0743 | 0.0398 | 0.0589 | 0.0703 |
| 0.7929 | 14.0 | 21 | 0.5661 | 0.0743 | 0.0398 | 0.0589 | 0.0703 |
| 0.7929 | 14.67 | 22 | 0.5652 | 0.0743 | 0.0398 | 0.0589 | 0.0703 |
| 0.7929 | 16.0 | 24 | 0.5636 | 0.0743 | 0.0398 | 0.0589 | 0.0703 |
| 0.7929 | 16.67 | 25 | 0.5630 | 0.0743 | 0.0398 | 0.0589 | 0.0703 |
| 0.7929 | 18.0 | 27 | 0.5621 | 0.0743 | 0.0398 | 0.0589 | 0.0703 |
| 0.7929 | 18.67 | 28 | 0.5619 | 0.0743 | 0.0398 | 0.0589 | 0.0703 |
| 0.7929 | 20.0 | 30 | 0.5617 | 0.0743 | 0.0398 | 0.0589 | 0.0703 |
### Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.17.0
- Tokenizers 0.15.1
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