---
license: apache-2.0
base_model: t5-base
tags:
- summarization
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-base-destination-inference
  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. -->

# t5-base-destination-inference

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0973
- Rouge1: 96.588
- Rouge2: 0.0
- Rougel: 96.588
- Rougelsum: 96.5792

## 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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 1.1906        | 1.0   | 5701  | 0.1466          | 94.1847 | 0.0    | 94.1672 | 94.1584   |
| 0.9407        | 2.0   | 11402 | 0.1228          | 94.632  | 0.0    | 94.6408 | 94.632    |
| 0.8533        | 3.0   | 17103 | 0.1106          | 95.4653 | 0.0    | 95.4653 | 95.4565   |
| 0.7889        | 4.0   | 22804 | 0.1017          | 95.8337 | 0.0    | 95.8249 | 95.8162   |
| 0.7394        | 5.0   | 28505 | 0.0990          | 96.2547 | 0.0    | 96.2591 | 96.2459   |
| 0.7014        | 6.0   | 34206 | 0.0986          | 96.3951 | 0.0    | 96.4038 | 96.3863   |
| 0.6737        | 7.0   | 39907 | 0.0966          | 96.4915 | 0.0    | 96.4872 | 96.474    |
| 0.6533        | 8.0   | 45608 | 0.0973          | 96.588  | 0.0    | 96.588  | 96.5792   |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3