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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: 42.4655
---
<!-- 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: 1.6732
- Rouge1: 42.4655
- Rouge2: 18.4875
- Rougel: 35.2198
- Rougelsum: 38.6465
- Gen Len: 16.8486
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.8853 | 0.22 | 100 | 1.7046 | 42.3969 | 18.365 | 35.0091 | 38.6527 | 16.6703 |
| 1.8463 | 0.43 | 200 | 1.6954 | 42.5607 | 18.4425 | 35.1088 | 38.8749 | 17.3565 |
| 1.8549 | 0.65 | 300 | 1.6794 | 42.5148 | 18.4716 | 35.1769 | 38.7018 | 17.1123 |
| 1.8361 | 0.87 | 400 | 1.6775 | 42.3899 | 18.4343 | 35.134 | 38.5732 | 16.6215 |
| 1.8132 | 1.08 | 500 | 1.6732 | 42.4655 | 18.4875 | 35.2198 | 38.6465 | 16.8486 |
| 1.8073 | 1.3 | 600 | 1.6708 | 42.4741 | 18.3824 | 35.1819 | 38.6066 | 16.9475 |
| 1.7973 | 1.52 | 700 | 1.6686 | 42.8206 | 18.7011 | 35.3874 | 38.9173 | 16.7595 |
| 1.798 | 1.74 | 800 | 1.6666 | 42.7779 | 18.6627 | 35.323 | 38.9467 | 16.9389 |
| 1.79 | 1.95 | 900 | 1.6668 | 42.8071 | 18.7113 | 35.2872 | 38.8641 | 16.9426 |
### Framework versions
- Transformers 4.36.0
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.15.0
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