---
license: apache-2.0
base_model: google/flan-t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: fine-tuned-flan-t5-20-epochs
  results: []
---

<!-- 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. -->

# fine-tuned-flan-t5-20-epochs

This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7842
- Rouge1: 0.2614
- Rouge2: 0.0824
- Rougel: 0.226
- Rougelsum: 0.2273
- Gen Len: 14.54

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 301  | 1.8551          | 0.1314 | 0.0425 | 0.1139 | 0.1139    | 11.4    |
| 2.7128        | 2.0   | 602  | 0.9826          | 0.1868 | 0.065  | 0.1564 | 0.1571    | 15.06   |
| 2.7128        | 3.0   | 903  | 0.8569          | 0.2079 | 0.0718 | 0.1716 | 0.1722    | 15.05   |
| 1.1113        | 4.0   | 1204 | 0.8300          | 0.2141 | 0.0705 | 0.181  | 0.181     | 14.59   |
| 0.9116        | 5.0   | 1505 | 0.8204          | 0.2254 | 0.0837 | 0.1943 | 0.1945    | 14.92   |
| 0.9116        | 6.0   | 1806 | 0.8116          | 0.243  | 0.0807 | 0.2074 | 0.2072    | 15.03   |
| 0.8732        | 7.0   | 2107 | 0.8082          | 0.2376 | 0.0752 | 0.2015 | 0.2016    | 14.83   |
| 0.8732        | 8.0   | 2408 | 0.8007          | 0.2345 | 0.0735 | 0.2015 | 0.2021    | 14.41   |
| 0.8336        | 9.0   | 2709 | 0.7968          | 0.2456 | 0.0757 | 0.2081 | 0.2081    | 14.4    |
| 0.8151        | 10.0  | 3010 | 0.7942          | 0.2544 | 0.0752 | 0.2134 | 0.2146    | 14.58   |
| 0.8151        | 11.0  | 3311 | 0.7924          | 0.2497 | 0.0783 | 0.2118 | 0.2124    | 14.5    |
| 0.8187        | 12.0  | 3612 | 0.7907          | 0.2552 | 0.0769 | 0.2189 | 0.2191    | 14.43   |
| 0.8187        | 13.0  | 3913 | 0.7891          | 0.258  | 0.077  | 0.2197 | 0.2199    | 14.37   |
| 0.8028        | 14.0  | 4214 | 0.7867          | 0.2511 | 0.0801 | 0.2146 | 0.2147    | 14.71   |
| 0.7793        | 15.0  | 4515 | 0.7852          | 0.2551 | 0.0777 | 0.2175 | 0.2177    | 14.67   |
| 0.7793        | 16.0  | 4816 | 0.7858          | 0.2594 | 0.0774 | 0.2219 | 0.2219    | 14.47   |
| 0.7872        | 17.0  | 5117 | 0.7850          | 0.2609 | 0.0803 | 0.2233 | 0.2244    | 14.56   |
| 0.7872        | 18.0  | 5418 | 0.7843          | 0.2599 | 0.0811 | 0.2242 | 0.2256    | 14.55   |
| 0.7756        | 19.0  | 5719 | 0.7844          | 0.261  | 0.0824 | 0.2256 | 0.2271    | 14.55   |
| 0.7752        | 20.0  | 6020 | 0.7842          | 0.2614 | 0.0824 | 0.226  | 0.2273    | 14.54   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0