---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- wikihow
metrics:
- rouge
model-index:
- name: wikihow_t5small_model
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: wikihow
      type: wikihow
      config: all
      split: test
      args: all
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.2067
---

<!-- 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. -->

# wikihow_t5small_model

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the wikihow dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9412
- Rouge1: 0.2067
- Rouge2: 0.0618
- Rougel: 0.17
- Rougelsum: 0.1698
- Gen Len: 18.864

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 3.4224        | 1.0   | 1250 | 3.0417          | 0.2045 | 0.0591 | 0.1659 | 0.1657    | 18.873  |
| 3.2253        | 2.0   | 2500 | 2.9721          | 0.2052 | 0.0603 | 0.168  | 0.1678    | 18.858  |
| 3.1943        | 3.0   | 3750 | 2.9477          | 0.2075 | 0.0621 | 0.1704 | 0.1701    | 18.876  |
| 3.1793        | 4.0   | 5000 | 2.9412          | 0.2067 | 0.0618 | 0.17   | 0.1698    | 18.864  |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0