---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
model-index:
- name: fastSUMMARIZER-t5-small-finetuned-on-xsum
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: xsum
      type: xsum
      config: default
      split: validation
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 31.3222
---

<!-- 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. -->

# fastSUMMARIZER-t5-small-finetuned-on-xsum

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the xsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2425
- Rouge1: 31.3222
- Rouge2: 10.0614
- Rougel: 25.0513
- Rougelsum: 25.0446
- Gen Len: 18.8044

## 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: 0.0002
- train_batch_size: 28
- eval_batch_size: 28
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.5078        | 1.0   | 7288  | 2.2860          | 30.9087 | 9.7673  | 24.6951 | 24.6927   | 18.7973 |
| 2.4245        | 2.0   | 14576 | 2.2425          | 31.3222 | 10.0614 | 25.0513 | 25.0446   | 18.8044 |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1