pytorch tensorboard t5 text2text-generation dataset:samsum transformers summarization generated_from_trainer license:apache-2.0 model-index autotrain_compatible
---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: t5-small-finetuned-samsum-en
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: samsum
      type: samsum
      args: samsum
    metrics:
    - name: Rouge1
      type: rouge
      value: 44.3313
  - task:
      type: summarization
      name: Summarization
    dataset:
      name: samsum
      type: samsum
      config: samsum
      split: test
    metrics:
    - name: ROUGE-1
      type: rouge
      value: 40.0386
      verified: true
    - name: ROUGE-2
      type: rouge
      value: 15.8501
      verified: true
    - name: ROUGE-L
      type: rouge
      value: 31.8084
      verified: true
    - name: ROUGE-LSUM
      type: rouge
      value: 36.0888
      verified: true
    - name: loss
      type: loss
      value: 2.1917073726654053
      verified: true
    - name: gen_len
      type: gen_len
      value: 18.1074
      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. -->

# t5-small-finetuned-samsum-en

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9335
- Rouge1: 44.3313
- Rouge2: 20.71
- Rougel: 37.221
- Rougelsum: 40.9603

## 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: 5.6e-05
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 1.4912        | 1.0   | 300  | 1.9043          | 44.1517 | 20.0186 | 36.6053 | 40.5164   |
| 1.5055        | 2.0   | 600  | 1.8912          | 44.1473 | 20.4456 | 37.069  | 40.6714   |
| 1.4852        | 3.0   | 900  | 1.8986          | 44.7536 | 20.8646 | 37.525  | 41.2189   |
| 1.4539        | 4.0   | 1200 | 1.9136          | 44.2144 | 20.3446 | 37.1088 | 40.7581   |
| 1.4262        | 5.0   | 1500 | 1.9215          | 44.2656 | 20.6044 | 37.3267 | 40.9469   |
| 1.4118        | 6.0   | 1800 | 1.9247          | 43.8793 | 20.4663 | 37.0614 | 40.6065   |
| 1.3987        | 7.0   | 2100 | 1.9256          | 43.9981 | 20.2703 | 36.7856 | 40.6354   |
| 1.3822        | 8.0   | 2400 | 1.9316          | 43.9732 | 20.4559 | 36.8039 | 40.5784   |
| 1.3773        | 9.0   | 2700 | 1.9314          | 44.3075 | 20.5435 | 37.0457 | 40.832    |
| 1.3795        | 10.0  | 3000 | 1.9335          | 44.3313 | 20.71   | 37.221  | 40.9603   |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
