---
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: []
pipeline_tag: summarization
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 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