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---
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: t5-finetuned-summarization-samsum
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: samsum
type: samsum
config: samsum
split: validation
args: samsum
metrics:
- name: Rouge1
type: rouge
value: 43.6894
---
<!-- 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-finetuned-summarization-samsum
This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6551
- Rouge1: 43.6894
- Rouge2: 21.0711
- Rougel: 36.7865
- Rougelsum: 40.2927
## 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: 5e-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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 2.0612 | 1.0 | 1842 | 1.7709 | 40.7189 | 17.9391 | 34.0848 | 37.86 |
| 1.8988 | 2.0 | 3684 | 1.7278 | 41.1985 | 18.7817 | 34.8297 | 38.378 |
| 1.8283 | 3.0 | 5526 | 1.6946 | 42.5298 | 19.6906 | 35.7159 | 39.2425 |
| 1.7798 | 4.0 | 7368 | 1.6860 | 42.9966 | 20.7335 | 36.5141 | 39.7994 |
| 1.7418 | 5.0 | 9210 | 1.6677 | 42.8533 | 20.4738 | 36.1407 | 39.5548 |
| 1.7157 | 6.0 | 11052 | 1.6645 | 43.6738 | 21.055 | 36.8091 | 40.3053 |
| 1.6896 | 7.0 | 12894 | 1.6584 | 43.5629 | 20.8972 | 36.614 | 40.2316 |
| 1.6756 | 8.0 | 14736 | 1.6567 | 43.8709 | 21.4421 | 36.9208 | 40.5036 |
| 1.6624 | 9.0 | 16578 | 1.6568 | 43.6278 | 21.0048 | 36.668 | 40.2666 |
| 1.6558 | 10.0 | 18420 | 1.6551 | 43.6894 | 21.0711 | 36.7865 | 40.2927 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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