---
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co./google/flan-t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6303
- Rouge1: 0.2243
- Rouge2: 0.0638
- Rougel: 0.1869
- Rougelsum: 0.1873

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|
| No log        | 1.0   | 3    | 2.8417          | 0.2288 | 0.0874 | 0.2003 | 0.2016    |
| No log        | 2.0   | 6    | 2.7634          | 0.2271 | 0.0883 | 0.1977 | 0.1967    |
| No log        | 3.0   | 9    | 2.6403          | 0.2144 | 0.0640 | 0.1852 | 0.1853    |
| No log        | 4.0   | 12   | 2.5802          | 0.2360 | 0.0760 | 0.2042 | 0.2060    |
| No log        | 5.0   | 15   | 2.5559          | 0.2321 | 0.0801 | 0.2019 | 0.2022    |
| No log        | 6.0   | 18   | 2.5504          | 0.2312 | 0.0793 | 0.2006 | 0.2028    |
| No log        | 7.0   | 21   | 2.5511          | 0.2338 | 0.0809 | 0.2032 | 0.2055    |
| No log        | 8.0   | 24   | 2.5562          | 0.2370 | 0.0813 | 0.2063 | 0.2078    |
| No log        | 9.0   | 27   | 2.5584          | 0.2370 | 0.0813 | 0.2063 | 0.2078    |
| No log        | 10.0  | 30   | 2.5568          | 0.2370 | 0.0813 | 0.2063 | 0.2078    |
| No log        | 11.0  | 33   | 2.5600          | 0.2370 | 0.0813 | 0.2063 | 0.2078    |
| No log        | 12.0  | 36   | 2.5662          | 0.2373 | 0.0804 | 0.1926 | 0.1910    |
| No log        | 13.0  | 39   | 2.5772          | 0.2430 | 0.0809 | 0.1991 | 0.1996    |
| No log        | 14.0  | 42   | 2.5900          | 0.2442 | 0.0813 | 0.1999 | 0.2005    |
| No log        | 15.0  | 45   | 2.5993          | 0.2436 | 0.0810 | 0.1988 | 0.1995    |
| No log        | 16.0  | 48   | 2.6078          | 0.2547 | 0.0810 | 0.2113 | 0.2128    |
| No log        | 17.0  | 51   | 2.6174          | 0.2391 | 0.0657 | 0.2035 | 0.2027    |
| No log        | 18.0  | 54   | 2.6243          | 0.2243 | 0.0638 | 0.1869 | 0.1873    |
| No log        | 19.0  | 57   | 2.6285          | 0.2243 | 0.0638 | 0.1869 | 0.1873    |
| No log        | 20.0  | 60   | 2.6303          | 0.2243 | 0.0638 | 0.1869 | 0.1873    |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2