|
--- |
|
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: 42.7055 |
|
--- |
|
|
|
<!-- 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: 1.6754 |
|
- Rouge1: 42.7055 |
|
- Rouge2: 18.3564 |
|
- Rougel: 35.2909 |
|
- Rougelsum: 38.9643 |
|
- Gen Len: 16.8474 |
|
|
|
## 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: 52 |
|
- eval_batch_size: 52 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
|
| 1.8824 | 0.35 | 100 | 1.7015 | 42.5036 | 18.333 | 35.1513 | 38.8251 | 16.6532 | |
|
| 1.8578 | 0.7 | 200 | 1.6878 | 42.0047 | 18.2467 | 35.0002 | 38.5021 | 16.7216 | |
|
| 1.835 | 1.06 | 300 | 1.6823 | 42.7828 | 18.6243 | 35.4419 | 38.9984 | 16.9048 | |
|
| 1.8144 | 1.41 | 400 | 1.6786 | 42.6579 | 18.3971 | 35.3512 | 38.9118 | 16.6618 | |
|
| 1.8094 | 1.76 | 500 | 1.6754 | 42.7055 | 18.3564 | 35.2909 | 38.9643 | 16.8474 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.36.0 |
|
- Pytorch 2.0.0 |
|
- Datasets 2.15.0 |
|
- Tokenizers 0.15.0 |
|
|
