---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
base_model: t5-small
model-index:
- name: t5-small-finetuned-samsum-en
  results:
  - task:
      type: text2text-generation
      name: Sequence-to-sequence Language Modeling
    dataset:
      name: samsum
      type: samsum
      args: samsum
    metrics:
    - type: rouge
      value: 44.3313
      name: Rouge1
  - task:
      type: summarization
      name: Summarization
    dataset:
      name: samsum
      type: samsum
      config: samsum
      split: test
    metrics:
    - type: rouge
      value: 40.0386
      name: ROUGE-1
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMmRlMjZmNjQyYWQ5MjcyM2M2MzUwMjk5ZTQxOTg3NzY1NjAxY2FkNzY5OGI2YjcxYTg1Y2M1Y2M2NDM2YmI1YSIsInZlcnNpb24iOjF9.xxrRepLefbFAUWkOJwOenMuwQ8g4i2QkEUgB_d1YsAv2aRRQd0vPfiGCMltGEtCxqrgQ6vmndOlkXIJhCPV9CQ
    - type: rouge
      value: 15.8501
      name: ROUGE-2
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYjQ4ZDQ0OTM2ZjI3NGExYWRjNWNjNTYwNjA0YWE0NWVkODJmODAwZTYzZjU3NzVhNjRiM2Y3ZDFhYjIwMTcxOSIsInZlcnNpb24iOjF9.UnymHQUy2s5P8yNUkFRhj6drPkKviYUNN2yB9E1KvYssNpRWnUbD5X_cVfYGWXVLPrtYe9dc-f7vSvm2Z1ZtDA
    - type: rouge
      value: 31.8084
      name: ROUGE-L
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMTllNjQ2MGRjMTJkNmI3OWI5MTNmNWJjNmUyMTU1ZjkxYzkyNDg4MWI2MGU1NWI5NmZhMTFjNjE4ZTI5M2MyMiIsInZlcnNpb24iOjF9.rVGbelDJoVmcTD6OOQ7O8C_4LhrMMuYUniY_hAmmgZ8kU_wgtApwi6Ms1sgzqtvbF0cDHaLxejE9XPZ8ZDZMAA
    - type: rouge
      value: 36.0888
      name: ROUGE-LSUM
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNWQyNmZmMjFkZTY2MDhjZmIzZDBkM2ZkYzUxZTcxMTcwMDVjMDdiMzljMjU2NDA5OTUxZTEwYzQwZjg2NDJmMiIsInZlcnNpb24iOjF9.ZEBUBcPLCURLXPN5upXDHaIVu_ilUEyvZd81nnppZCWEuULyp30jcpmzLFb91v0WwRHMDPIjPl0hlckzq71ICw
    - type: loss
      value: 2.1917073726654053
      name: loss
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNjA0MDk3MWZiMDgxMDlkZDFjY2UwODM0MTk4MmY2NzlkNThmYTA0ODk5MzgyZWQwYjVlZGFlZmJmNjA2NDA2ZSIsInZlcnNpb24iOjF9.Wc_5Wpf_Wa0Xm0A7w2EYnF1_eQ-2QU_v6eXr8SHveBszH5YhZBW6GS3yKslVVKKIaAGSGKtLIHzMW1H-NqqNDA
    - type: gen_len
      value: 18.1074
      name: gen_len
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNDFlMmU0MTAyMDM5M2UyZDA2N2U4MjQ3MjhjYjdkOGY1ODdlNDY1NWY3NTQ3MzBhOWE3OTk2ZGU3ZTYyNjU1ZCIsInZlcnNpb24iOjF9.Ob1cLE1iYpV00ae1RYRIUNZz7V-x8IYTcU6ofR5gf07PdRqfiOgZtpV0tN3yM0_nyAJI71J8fnC6yWq10Y0HBw
---

<!-- 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