flan-t5-base-samsum / README.md
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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: 47.6387
---
<!-- 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: 1.3737
- Rouge1: 47.6387
- Rouge2: 24.1608
- Rougel: 40.1108
- Rougelsum: 43.9213
- Gen Len: 17.2076
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.453 | 1.0 | 1842 | 1.3864 | 47.0319 | 22.9684 | 39.1486 | 42.9635 | 17.3797 |
| 1.3399 | 2.0 | 3684 | 1.3758 | 47.1982 | 23.4772 | 39.756 | 43.4967 | 17.1954 |
| 1.268 | 3.0 | 5526 | 1.3782 | 47.5188 | 23.9509 | 39.9305 | 43.7792 | 17.3822 |
| 1.2313 | 4.0 | 7368 | 1.3737 | 47.6387 | 24.1608 | 40.1108 | 43.9213 | 17.2076 |
| 1.206 | 5.0 | 9210 | 1.3764 | 47.7288 | 23.9829 | 40.1887 | 43.9615 | 17.2857 |
### Framework versions
- Transformers 4.36.0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0