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---
library_name: transformers
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
model-index:
- name: t5-small-finetuned-xsum
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: xsum
type: xsum
config: default
split: validation
args: default
metrics:
- name: Rouge1
type: rouge
value: 26.2006
---
<!-- 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-xsum
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the xsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6282
- Rouge1: 26.2006
- Rouge2: 6.4986
- Rougel: 20.4525
- Rougelsum: 20.4233
- Gen Len: 18.791
## 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: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 3.0796 | 1.0 | 500 | 2.6971 | 23.5102 | 5.0088 | 18.4369 | 18.4317 | 18.719 |
| 2.8953 | 2.0 | 1000 | 2.6563 | 25.1823 | 5.9526 | 19.6696 | 19.6505 | 18.779 |
| 2.8527 | 3.0 | 1500 | 2.6393 | 25.7775 | 6.2129 | 20.1822 | 20.1652 | 18.79 |
| 2.8301 | 4.0 | 2000 | 2.6307 | 25.899 | 6.2538 | 20.2373 | 20.222 | 18.802 |
| 2.8158 | 5.0 | 2500 | 2.6282 | 26.2006 | 6.4986 | 20.4525 | 20.4233 | 18.791 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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