---
license: apache-2.0
base_model: google/long-t5-tglobal-base
tags:
- summarization
- generated_from_trainer
datasets:
- gov_report_summarization_dataset
metrics:
- rouge
model-index:
- name: long-t5-tglobal-base-finetuned-govReport-4096
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: gov_report_summarization_dataset
      type: gov_report_summarization_dataset
      config: document
      split: validation
      args: document
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.0463
---

<!-- 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-finetuned-govReport-4096

This model is a fine-tuned version of [google/long-t5-tglobal-base](https://huggingface.co/google/long-t5-tglobal-base) on the gov_report_summarization_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3116
- Rouge1: 0.0463
- Rouge2: 0.0231
- Rougel: 0.039
- Rougelsum: 0.0436

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| 14.9489       | 1.0   | 25   | 2.8019          | 0.0416 | 0.0156 | 0.0343 | 0.0383    |
| 3.9751        | 2.0   | 50   | 2.0899          | 0.0396 | 0.0145 | 0.0332 | 0.0367    |
| 3.0361        | 3.0   | 75   | 1.4337          | 0.0395 | 0.0138 | 0.033  | 0.0366    |
| 1.8477        | 4.0   | 100  | 1.3654          | 0.0406 | 0.0157 | 0.0342 | 0.0378    |
| 1.6709        | 5.0   | 125  | 1.3355          | 0.0419 | 0.0171 | 0.036  | 0.0394    |
| 1.5673        | 6.0   | 150  | 1.3229          | 0.0446 | 0.022  | 0.0383 | 0.0423    |
| 1.5567        | 7.0   | 175  | 1.3181          | 0.047  | 0.0233 | 0.0393 | 0.0441    |
| 1.5066        | 8.0   | 200  | 1.3135          | 0.0467 | 0.0233 | 0.0394 | 0.0441    |
| 1.515         | 9.0   | 225  | 1.3117          | 0.0462 | 0.0231 | 0.0389 | 0.0436    |
| 1.4868        | 10.0  | 250  | 1.3116          | 0.0463 | 0.0231 | 0.039  | 0.0436    |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1