---
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: 0.5356
- Rouge1: 0.0844
- Rouge2: 0.0543
- Rougel: 0.0716
- Rougelsum: 0.0842

## 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: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| No log        | 0.67  | 1    | 0.6583          | 0.0647 | 0.03   | 0.0504 | 0.0595    |
| No log        | 2.0   | 3    | 0.6232          | 0.067  | 0.036  | 0.0527 | 0.0643    |
| No log        | 2.67  | 4    | 0.6134          | 0.067  | 0.036  | 0.0527 | 0.0643    |
| No log        | 4.0   | 6    | 0.5971          | 0.0742 | 0.0426 | 0.0654 | 0.0735    |
| No log        | 4.67  | 7    | 0.5897          | 0.0765 | 0.0462 | 0.0654 | 0.0762    |
| No log        | 6.0   | 9    | 0.5777          | 0.0803 | 0.0486 | 0.0665 | 0.0802    |
| No log        | 6.67  | 10   | 0.5729          | 0.0813 | 0.0498 | 0.0677 | 0.0801    |
| No log        | 8.0   | 12   | 0.5652          | 0.0813 | 0.0498 | 0.0677 | 0.0801    |
| No log        | 8.67  | 13   | 0.5622          | 0.0823 | 0.0544 | 0.0685 | 0.0811    |
| No log        | 10.0  | 15   | 0.5575          | 0.0823 | 0.0544 | 0.0685 | 0.0811    |
| No log        | 10.67 | 16   | 0.5559          | 0.0823 | 0.0544 | 0.0685 | 0.0811    |
| No log        | 12.0  | 18   | 0.5528          | 0.0823 | 0.0544 | 0.0685 | 0.0811    |
| No log        | 12.67 | 19   | 0.5513          | 0.0823 | 0.0544 | 0.0685 | 0.0811    |
| 0.7235        | 14.0  | 21   | 0.5488          | 0.0823 | 0.0544 | 0.0685 | 0.0811    |
| 0.7235        | 14.67 | 22   | 0.5476          | 0.0811 | 0.0544 | 0.0674 | 0.0794    |
| 0.7235        | 16.0  | 24   | 0.5451          | 0.086  | 0.0574 | 0.074  | 0.0841    |
| 0.7235        | 16.67 | 25   | 0.5438          | 0.086  | 0.0574 | 0.074  | 0.0841    |
| 0.7235        | 18.0  | 27   | 0.5420          | 0.086  | 0.0574 | 0.074  | 0.0841    |
| 0.7235        | 18.67 | 28   | 0.5412          | 0.086  | 0.0574 | 0.074  | 0.0841    |
| 0.7235        | 20.0  | 30   | 0.5397          | 0.086  | 0.0574 | 0.074  | 0.0841    |
| 0.7235        | 20.67 | 31   | 0.5390          | 0.086  | 0.0574 | 0.074  | 0.0841    |
| 0.7235        | 22.0  | 33   | 0.5377          | 0.0844 | 0.0543 | 0.0716 | 0.0842    |
| 0.7235        | 22.67 | 34   | 0.5372          | 0.0844 | 0.0543 | 0.0716 | 0.0842    |
| 0.7235        | 24.0  | 36   | 0.5363          | 0.0844 | 0.0543 | 0.0716 | 0.0842    |
| 0.7235        | 24.67 | 37   | 0.5360          | 0.0844 | 0.0543 | 0.0716 | 0.0842    |
| 0.7235        | 26.0  | 39   | 0.5357          | 0.0844 | 0.0543 | 0.0716 | 0.0842    |
| 0.6478        | 26.67 | 40   | 0.5356          | 0.0844 | 0.0543 | 0.0716 | 0.0842    |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.17.0
- Tokenizers 0.15.1