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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: test
args: samsum
metrics:
- name: Rouge1
type: rouge
value: 47.39
---
<!-- 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: 1.3707
- Rouge1: 47.39
- Rouge2: 23.8837
- Rougel: 40.08
- Rougelsum: 43.7241
- Gen Len: 17.2137
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.4525 | 1.0 | 1842 | 1.3837 | 46.4021 | 22.8734 | 39.1025 | 42.8284 | 17.2149 |
| 1.3436 | 2.0 | 3684 | 1.3725 | 47.0983 | 23.5269 | 39.8757 | 43.4526 | 17.1954 |
| 1.2821 | 3.0 | 5526 | 1.3708 | 47.2332 | 23.6343 | 39.7749 | 43.4436 | 17.2271 |
| 1.2307 | 4.0 | 7368 | 1.3707 | 47.39 | 23.8837 | 40.08 | 43.7241 | 17.2137 |
| 1.1986 | 5.0 | 9210 | 1.3762 | 47.4841 | 23.9306 | 40.0741 | 43.7225 | 17.2821 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.0.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.0
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