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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: 42.6378
---
<!-- 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: 1.6629
- Rouge1: 42.6378
- Rouge2: 18.2896
- Rougel: 35.1851
- Rougelsum: 38.8113
- Gen Len: 16.8596
## 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: 40
- eval_batch_size: 40
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.7932 | 0.27 | 100 | 1.6830 | 42.7032 | 18.4803 | 35.278 | 38.9331 | 17.0403 |
| 1.8102 | 0.54 | 200 | 1.6701 | 42.2811 | 18.2246 | 35.0893 | 38.4619 | 16.7265 |
| 1.8279 | 0.81 | 300 | 1.6658 | 42.6465 | 18.6939 | 35.4208 | 38.9399 | 16.8120 |
| 1.802 | 1.08 | 400 | 1.6633 | 42.5867 | 18.3579 | 35.3253 | 38.7049 | 16.6862 |
| 1.773 | 1.36 | 500 | 1.6629 | 42.6378 | 18.2896 | 35.1851 | 38.8113 | 16.8596 |
| 1.7752 | 1.63 | 600 | 1.6598 | 42.7111 | 18.3689 | 35.4218 | 38.8698 | 16.9328 |
| 1.7688 | 1.9 | 700 | 1.6589 | 42.6972 | 18.3536 | 35.3153 | 38.7976 | 17.0073 |
### Framework versions
- Transformers 4.36.0
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.15.0
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