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---
license: apache-2.0
base_model: google/flan-t5-small
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: flan-t5-small-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: 42.6222
---
<!-- 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-small-samsum
This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6729
- Rouge1: 42.6222
- Rouge2: 18.682
- Rougel: 35.3954
- Rougelsum: 38.9104
- Gen Len: 16.9170
## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.8863 | 0.22 | 100 | 1.7049 | 42.1145 | 18.0254 | 34.733 | 38.4052 | 16.5788 |
| 1.8463 | 0.43 | 200 | 1.6947 | 42.4119 | 18.2925 | 34.9702 | 38.8535 | 17.3614 |
| 1.8548 | 0.65 | 300 | 1.6792 | 42.5967 | 18.5244 | 35.1965 | 38.9087 | 17.1514 |
| 1.8358 | 0.87 | 400 | 1.6772 | 42.167 | 18.2032 | 34.8647 | 38.4144 | 16.5873 |
| 1.8129 | 1.08 | 500 | 1.6729 | 42.6222 | 18.682 | 35.3954 | 38.9104 | 16.9170 |
| 1.8068 | 1.3 | 600 | 1.6709 | 42.5238 | 18.311 | 35.1257 | 38.6584 | 16.9451 |
| 1.7973 | 1.52 | 700 | 1.6687 | 42.8715 | 18.6133 | 35.3054 | 38.971 | 16.7546 |
| 1.7979 | 1.74 | 800 | 1.6668 | 42.9038 | 18.7483 | 35.4156 | 39.1118 | 16.8791 |
| 1.7899 | 1.95 | 900 | 1.6670 | 43.1142 | 18.7369 | 35.4796 | 39.2724 | 16.9109 |
### Framework versions
- Transformers 4.36.0
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.15.0
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