transformers tensorboard safetensors t5 text2text-generation generated_from_trainer base_model:google-t5/t5-base base_model:finetune:google-t5/t5-base license:apache-2.0 autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: t5-base
license: apache-2.0
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: t5-base_readme_summarization
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# t5-base_readme_summarization

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: 1.7573
- Rouge1: 0.4859
- Rouge2: 0.3402
- Rougel: 0.4581
- Rougelsum: 0.4581
- Gen Len: 14.1882

## 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: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.1761        | 1.0   | 1458 | 1.8974          | 0.4769 | 0.3281 | 0.4486 | 0.4484    | 14.265  |
| 1.9982        | 2.0   | 2916 | 1.8329          | 0.4819 | 0.3349 | 0.4553 | 0.4552    | 14.0492 |
| 1.8626        | 3.0   | 4374 | 1.7946          | 0.4793 | 0.3343 | 0.4528 | 0.4529    | 14.5971 |
| 1.8013        | 4.0   | 5832 | 1.7695          | 0.4873 | 0.3418 | 0.4609 | 0.4614    | 14.1691 |
| 1.7478        | 5.0   | 7290 | 1.7573          | 0.4859 | 0.3402 | 0.4581 | 0.4581    | 14.1882 |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
