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

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/theubaada/huggingface/runs/iqgj3vcb)
# long-t5-tglobal-base

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: 1.9401
- Rouge1: 0.1934
- Rouge2: 0.0269
- Rougel: 0.1151

## 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: 4e-05
- train_batch_size: 8
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 13

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rouge1 | Rouge2 | Rougel |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|
| 1.5731        | 0.9996 | 600  | 1.9730          | 0.1342 | 0.0151 | 0.0912 |
| 1.3694        | 1.9996 | 1200 | 1.9623          | 0.1371 | 0.0175 | 0.0909 |
| 1.9561        | 2.9992 | 1800 | 1.9565          | 0.1423 | 0.0178 | 0.0928 |
| 1.0882        | 3.9996 | 2400 | 1.9548          | 0.1417 | 0.0186 | 0.0900 |
| 1.4872        | 4.9992 | 3000 | 1.9412          | 0.1581 | 0.0212 | 0.1006 |
| 1.4126        | 5.9988 | 3600 | 1.9486          | 0.1589 | 0.0188 | 0.0986 |
| 1.1634        | 7.0    | 4201 | 1.9464          | 0.1756 | 0.0229 | 0.1046 |
| 0.9541        | 7.9996 | 4801 | 1.9401          | 0.1791 | 0.0243 | 0.1078 |
| 0.9153        | 8.9975 | 5400 | 1.9401          | 0.1934 | 0.0269 | 0.1151 |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.2.0
- Datasets 2.19.1
- Tokenizers 0.19.1