---
library_name: transformers
license: apache-2.0
base_model: google/long-t5-tglobal-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: my_awesome_dailymail_long_model
  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. -->

# my_awesome_dailymail_long_model

This model is a fine-tuned version of [google/long-t5-tglobal-base](https://huggingface.co/google/long-t5-tglobal-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6759
- Rouge1: 0.2345
- Rouge2: 0.0986
- Rougel: 0.1918
- Rougelsum: 0.1921
- Gen Len: 18.999

## 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: 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: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.5452        | 0.5   | 500  | 1.7971          | 0.227  | 0.0911 | 0.1815 | 0.1815    | 18.9695 |
| 2.2571        | 1.0   | 1000 | 1.7336          | 0.2315 | 0.0941 | 0.1865 | 0.1865    | 18.995  |
| 2.1671        | 1.5   | 1500 | 1.7149          | 0.2322 | 0.0958 | 0.1885 | 0.1887    | 18.995  |
| 2.1123        | 2.0   | 2000 | 1.6973          | 0.2343 | 0.0967 | 0.1903 | 0.1904    | 18.999  |
| 2.0778        | 2.5   | 2500 | 1.6900          | 0.2349 | 0.0974 | 0.1913 | 0.1914    | 18.999  |
| 2.0609        | 3.0   | 3000 | 1.6833          | 0.2342 | 0.098  | 0.1914 | 0.1916    | 18.999  |
| 2.0466        | 3.5   | 3500 | 1.6780          | 0.2344 | 0.0983 | 0.1918 | 0.192     | 18.999  |
| 2.0454        | 4.0   | 4000 | 1.6759          | 0.2345 | 0.0986 | 0.1918 | 0.1921    | 18.999  |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 3.0.0
- Tokenizers 0.19.1