transformers tensorboard safetensors t5 text2text-generation summarization generated_from_trainer base_model:google-t5/t5-small base_model:finetune:google-t5/t5-small license:apache-2.0 autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: t5-small
library_name: transformers
license: apache-2.0
metrics:
- rouge
tags:
- summarization
- generated_from_trainer
model-index:
- name: t5-small-finetuned-cnn-news
  results: []
---

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

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3455
- Rouge1: 25.2386
- Rouge2: 9.5343
- Rougel: 20.6686
- Rougelsum: 23.2614

## 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: 0.00056
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 1.1393        | 1.0   | 718  | 2.4712          | 23.3266 | 8.6693 | 18.9609 | 21.406    |
| 1.7054        | 2.0   | 1436 | 2.2697          | 24.3337 | 9.4775 | 20.1514 | 22.5425   |
| 1.5479        | 3.0   | 2154 | 2.2868          | 24.3861 | 9.0245 | 20.0315 | 22.582    |
| 1.4377        | 4.0   | 2872 | 2.3311          | 25.0473 | 9.4761 | 20.4587 | 23.0242   |
| 1.3533        | 5.0   | 3590 | 2.3455          | 25.2386 | 9.5343 | 20.6686 | 23.2614   |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
