transformers tensorboard safetensors t5 text2text-generation generated_from_trainer base_model:ericjiliangli/t5-small-news-summarization base_model:finetune:ericjiliangli/t5-small-news-summarization autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: ericjiliangli/t5-small-news-summarization
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: t5-small-finetuned-2024-03-12
  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-small-finetuned-2024-03-12

This model is a fine-tuned version of [ericjiliangli/t5-small-news-summarization](https://huggingface.co/ericjiliangli/t5-small-news-summarization) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7445
- Rouge1: 30.158
- Rouge2: 15.0234
- Rougel: 25.9885
- Rougelsum: 26.1101
- Gen Len: 18.759

## 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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:-------:|:---------:|:-------:|
| 1.9214        | 1.0   | 328  | 1.7445          | 30.158 | 15.0234 | 25.9885 | 26.1101   | 18.759  |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
