---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
base_model: google/flan-t5-base
model-index:
- name: flan-t5-base-xsum
  results:
  - task:
      type: text2text-generation
      name: Sequence-to-sequence Language Modeling
    dataset:
      name: xsum
      type: xsum
      config: default
      split: test
      args: default
    metrics:
    - type: rouge
      value: 32.3503
      name: Rouge1
---

<!-- 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. -->

# flan-t5-base-xsum

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the xsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0798
- Rouge1: 32.3503
- Rouge2: 10.8909
- Rougel: 25.9346
- Rougelsum: 25.9216
- Gen Len: 18.8494

## 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: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adafactor
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.335         | 1.0   | 1417 | 2.0823          | 31.3453 | 10.2077 | 25.0051 | 25.008    | 18.8259 |
| 1.8642        | 2.0   | 2834 | 2.0798          | 32.3503 | 10.8909 | 25.9346 | 25.9216   | 18.8494 |
| 1.5208        | 3.0   | 4251 | 2.1272          | 32.6743 | 11.3394 | 26.3776 | 26.3724   | 18.8435 |
| 1.2628        | 4.0   | 5668 | 2.2110          | 32.695  | 11.3273 | 26.3215 | 26.322    | 18.8306 |
| 1.0649        | 5.0   | 7085 | 2.3143          | 32.5287 | 11.3662 | 26.274  | 26.2741   | 18.8345 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.0
- Tokenizers 0.13.2