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---
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: flan-t5-base-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: 48.3584
---
<!-- 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. -->
# flan-t5-base-samsum
This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3808
- Rouge1: 48.3584
- Rouge2: 25.2355
- Rougel: 41.0959
- Rougelsum: 44.8827
- Gen Len: 17.3496
## 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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.4515 | 1.0 | 1842 | 1.3930 | 47.8577 | 24.5602 | 40.427 | 44.374 | 17.4487 |
| 1.346 | 2.0 | 3684 | 1.3809 | 48.1527 | 24.809 | 40.8549 | 44.5684 | 17.4633 |
| 1.2806 | 3.0 | 5526 | 1.3817 | 48.2629 | 25.0493 | 40.952 | 44.6847 | 17.3704 |
| 1.2414 | 4.0 | 7368 | 1.3799 | 48.2785 | 25.1137 | 41.1032 | 44.7977 | 17.3778 |
| 1.2081 | 5.0 | 9210 | 1.3808 | 48.3584 | 25.2355 | 41.0959 | 44.8827 | 17.3496 |
### Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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