transformers pytorch longt5 text2text-generation generated_from_trainer dataset:learn3r/gov_report_memsum_bp base_model:google/long-t5-tglobal-xl license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: google/long-t5-tglobal-xl
tags:
- generated_from_trainer
datasets:
- learn3r/gov_report_memsum_bp
metrics:
- rouge
model-index:
- name: longt5_xl_gov_memsum_bp_5
  results:
  - task:
      name: Summarization
      type: summarization
    dataset:
      name: learn3r/gov_report_memsum_bp
      type: learn3r/gov_report_memsum_bp
    metrics:
    - name: Rouge1
      type: rouge
      value: 55.1149
---

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# longt5_xl_gov_memsum_bp_5

This model is a fine-tuned version of [google/long-t5-tglobal-xl](https://huggingface.co/google/long-t5-tglobal-xl) on the learn3r/gov_report_memsum_bp dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9813
- Rouge1: 55.1149
- Rouge2: 30.149
- Rougel: 31.9694
- Rougelsum: 52.9549
- Gen Len: 1101.6060

## 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: 0.001
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len   |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:---------:|
| 1.1562        | 1.0   | 272  | 1.0105          | 37.2934 | 18.6683 | 24.0563 | 35.6575   | 1844.1543 |
| 0.9737        | 2.0   | 545  | 0.9813          | 55.1149 | 30.149  | 31.9694 | 52.9549   | 1101.6060 |
| 0.8395        | 3.0   | 818  | 0.9925          | 57.4498 | 31.9315 | 32.914  | 55.2389   | 1055.9784 |
| 0.7353        | 4.0   | 1091 | 1.0404          | 67.3946 | 39.2034 | 36.8583 | 64.9879   | 829.2881  |
| 0.6212        | 4.99  | 1360 | 1.0752          | 64.5433 | 36.9477 | 35.3482 | 62.2005   | 779.6152  |


### Framework versions

- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
