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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-farag
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: 47.4352
---
<!-- 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-farag
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: 1.3695
- Rouge1: 47.4352
- Rouge2: 23.613
- Rougel: 39.8977
- Rougelsum: 43.5852
- Gen Len: 17.3529
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.4497 | 1.0 | 1842 | 1.3848 | 46.3358 | 22.5925 | 38.7161 | 42.6084 | 17.2918 |
| 1.3474 | 2.0 | 3684 | 1.3717 | 47.1291 | 23.2809 | 39.4633 | 43.3246 | 17.2735 |
| 1.2818 | 3.0 | 5526 | 1.3701 | 47.349 | 23.4894 | 39.7933 | 43.4507 | 17.2479 |
| 1.2285 | 4.0 | 7368 | 1.3695 | 47.4352 | 23.613 | 39.8977 | 43.5852 | 17.3529 |
| 1.196 | 5.0 | 9210 | 1.3735 | 47.3488 | 23.6475 | 39.6788 | 43.523 | 17.3138 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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