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---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: t5-small-finetuned-samsum-en
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: samsum
type: samsum
args: samsum
metrics:
- name: Rouge1
type: rouge
value: 44.3313
---
<!-- 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-samsum-en
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9335
- Rouge1: 44.3313
- Rouge2: 20.71
- Rougel: 37.221
- Rougelsum: 40.9603
## 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: 5.6e-05
- train_batch_size: 10
- eval_batch_size: 10
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 1.4912 | 1.0 | 300 | 1.9043 | 44.1517 | 20.0186 | 36.6053 | 40.5164 |
| 1.5055 | 2.0 | 600 | 1.8912 | 44.1473 | 20.4456 | 37.069 | 40.6714 |
| 1.4852 | 3.0 | 900 | 1.8986 | 44.7536 | 20.8646 | 37.525 | 41.2189 |
| 1.4539 | 4.0 | 1200 | 1.9136 | 44.2144 | 20.3446 | 37.1088 | 40.7581 |
| 1.4262 | 5.0 | 1500 | 1.9215 | 44.2656 | 20.6044 | 37.3267 | 40.9469 |
| 1.4118 | 6.0 | 1800 | 1.9247 | 43.8793 | 20.4663 | 37.0614 | 40.6065 |
| 1.3987 | 7.0 | 2100 | 1.9256 | 43.9981 | 20.2703 | 36.7856 | 40.6354 |
| 1.3822 | 8.0 | 2400 | 1.9316 | 43.9732 | 20.4559 | 36.8039 | 40.5784 |
| 1.3773 | 9.0 | 2700 | 1.9314 | 44.3075 | 20.5435 | 37.0457 | 40.832 |
| 1.3795 | 10.0 | 3000 | 1.9335 | 44.3313 | 20.71 | 37.221 | 40.9603 |
### Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
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