---
library_name: transformers
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
datasets:
- eli5_category
metrics:
- rouge
model-index:
- name: flan-t5-base-finetuned-t5
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: eli5_category
      type: eli5_category
      config: default
      split: validation1
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 10.1877
---

<!-- 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-finetuned-t5

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the eli5_category dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Rouge1: 10.1877
- Rouge2: 0.0
- Rougel: 10.1808
- Rougelsum: 10.1824
- Gen Len: 9.366

## 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: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 0.0           | 1.0   | 5736  | nan             | 10.1877 | 0.0    | 10.1808 | 10.1824   | 9.366   |
| 0.0           | 2.0   | 11472 | nan             | 10.1877 | 0.0    | 10.1808 | 10.1824   | 9.366   |
| 0.0           | 3.0   | 17208 | nan             | 10.1877 | 0.0    | 10.1808 | 10.1824   | 9.366   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1