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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: []
pipeline_tag: summarization
---
<!-- 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: 0.5356
- 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 |