transformers safetensors t5 text2text-generation Summarization generated_from_trainer summarization base_model:RMWeerasinghe/t5-small-finetuned-govReport-3072 base_model:finetune:RMWeerasinghe/t5-small-finetuned-govReport-3072 license:apache-2.0 autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: RMWeerasinghe/t5-small-finetuned-govReport-3072
license: apache-2.0
metrics:
- rouge
pipeline_tag: summarization
tags:
- Summarization
- generated_from_trainer
model-index:
- name: t5-small-govReport-boardpapers-3072
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# t5-small-govReport-boardpapers-3072

This model is a fine-tuned version of [RMWeerasinghe/t5-small-finetuned-govReport-3072](https://huggingface.co/RMWeerasinghe/t5-small-finetuned-govReport-3072) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.6701
- Rouge1: 0.0443
- Rouge2: 0.0194
- Rougel: 0.0382
- Rougelsum: 0.0443

## 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    | 3.9496          | 0.0584 | 0.0214 | 0.0482 | 0.0572    |
| No log        | 2.0   | 3    | 3.9252          | 0.0562 | 0.0223 | 0.0463 | 0.0562    |
| No log        | 2.67  | 4    | 3.9121          | 0.0597 | 0.0223 | 0.0485 | 0.0596    |
| No log        | 4.0   | 6    | 3.8880          | 0.0597 | 0.0223 | 0.0485 | 0.0596    |
| No log        | 4.67  | 7    | 3.8755          | 0.0597 | 0.0223 | 0.0485 | 0.0596    |
| No log        | 6.0   | 9    | 3.8506          | 0.0597 | 0.0223 | 0.0485 | 0.0596    |
| No log        | 6.67  | 10   | 3.8395          | 0.0553 | 0.0197 | 0.0441 | 0.0541    |
| No log        | 8.0   | 12   | 3.8172          | 0.0582 | 0.0262 | 0.049  | 0.057     |
| No log        | 8.67  | 13   | 3.8065          | 0.0582 | 0.0262 | 0.049  | 0.057     |
| No log        | 10.0  | 15   | 3.7862          | 0.0582 | 0.0257 | 0.049  | 0.057     |
| No log        | 10.67 | 16   | 3.7769          | 0.057  | 0.0262 | 0.049  | 0.0556    |
| No log        | 12.0  | 18   | 3.7599          | 0.0577 | 0.0294 | 0.0495 | 0.0575    |
| No log        | 12.67 | 19   | 3.7522          | 0.0487 | 0.0174 | 0.042  | 0.0474    |
| 4.3528        | 14.0  | 21   | 3.7378          | 0.048  | 0.0155 | 0.0406 | 0.0461    |
| 4.3528        | 14.67 | 22   | 3.7310          | 0.0536 | 0.0206 | 0.0421 | 0.0511    |
| 4.3528        | 16.0  | 24   | 3.7187          | 0.048  | 0.017  | 0.0394 | 0.0448    |
| 4.3528        | 16.67 | 25   | 3.7132          | 0.043  | 0.017  | 0.0374 | 0.041     |
| 4.3528        | 18.0  | 27   | 3.7031          | 0.043  | 0.017  | 0.0374 | 0.041     |
| 4.3528        | 18.67 | 28   | 3.6985          | 0.043  | 0.017  | 0.0374 | 0.041     |
| 4.3528        | 20.0  | 30   | 3.6905          | 0.043  | 0.017  | 0.0374 | 0.041     |
| 4.3528        | 20.67 | 31   | 3.6869          | 0.043  | 0.017  | 0.0374 | 0.041     |
| 4.3528        | 22.0  | 33   | 3.6807          | 0.0442 | 0.0194 | 0.0381 | 0.0423    |
| 4.3528        | 22.67 | 34   | 3.6781          | 0.0442 | 0.0194 | 0.0381 | 0.0423    |
| 4.3528        | 24.0  | 36   | 3.6740          | 0.0442 | 0.0194 | 0.0381 | 0.0423    |
| 4.3528        | 24.67 | 37   | 3.6725          | 0.0442 | 0.0194 | 0.0381 | 0.0423    |
| 4.3528        | 26.0  | 39   | 3.6705          | 0.0443 | 0.0194 | 0.0382 | 0.0443    |
| 4.0602        | 26.67 | 40   | 3.6701          | 0.0443 | 0.0194 | 0.0382 | 0.0443    |


### Framework versions

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