---
license: cc-by-nc-sa-4.0
tags:
- generated_from_trainer
- longt5
- summarization
model-index:
- name: longt5-mediasum
  results:
  - task:
      type: summarization
      name: Summarization
    dataset:
      name: xsum
      type: xsum
      config: default
      split: test
    metrics:
    - name: ROUGE-1
      type: rouge
      value: 22.7044
      verified: true
    - name: ROUGE-2
      type: rouge
      value: 5.616
      verified: true
    - name: ROUGE-L
      type: rouge
      value: 18.0111
      verified: true
    - name: ROUGE-LSUM
      type: rouge
      value: 18.1554
      verified: true
    - name: loss
      type: loss
      value: 2.1656227111816406
      verified: true
    - name: gen_len
      type: gen_len
      value: 18.3527
      verified: true
  - task:
      type: summarization
      name: Summarization
    dataset:
      name: cnn_dailymail
      type: cnn_dailymail
      config: 3.0.0
      split: test
    metrics:
    - name: ROUGE-1
      type: rouge
      value: 21.1522
      verified: true
    - name: ROUGE-2
      type: rouge
      value: 8.1315
      verified: true
    - name: ROUGE-L
      type: rouge
      value: 16.6625
      verified: true
    - name: ROUGE-LSUM
      type: rouge
      value: 19.3603
      verified: true
    - name: loss
      type: loss
      value: 1.899269700050354
      verified: true
    - name: gen_len
      type: gen_len
      value: 17.853
      verified: true
---

<!-- 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. -->

# longt5-mediasum

This model is a fine-tuned version of [google/long-t5-tglobal-base](https://huggingface.co/google/long-t5-tglobal-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0129

## 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: 5e-05
- train_batch_size: 12
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.66          | 1.0   | 1667 | 2.0643          |
| 2.472         | 2.0   | 3334 | 2.0241          |
| 2.3574        | 3.0   | 5001 | 2.0129          |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0a0+17540c5
- Datasets 2.3.2
- Tokenizers 0.12.1