|
--- |
|
license: apache-2.0 |
|
tags: |
|
- summarization |
|
- generated_from_trainer |
|
datasets: |
|
- cnn_dailymail |
|
metrics: |
|
- rouge |
|
model-index: |
|
- name: t5-small-finetuned-cnn |
|
results: |
|
- task: |
|
name: Sequence-to-sequence Language Modeling |
|
type: text2text-generation |
|
dataset: |
|
name: cnn_dailymail |
|
type: cnn_dailymail |
|
args: 3.0.0 |
|
metrics: |
|
- name: Rouge1 |
|
type: rouge |
|
value: 33.2082 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# t5-small-finetuned-cnn |
|
|
|
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the cnn_dailymail dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.8436 |
|
- Rouge1: 33.2082 |
|
- Rouge2: 16.798 |
|
- Rougel: 28.9573 |
|
- Rougelsum: 31.1044 |
|
|
|
## 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: 5.6e-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: 8 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:| |
|
| 2.3793 | 1.0 | 359 | 1.8885 | 33.0321 | 16.7798 | 28.9367 | 30.9509 | |
|
| 2.1432 | 2.0 | 718 | 1.8481 | 33.1559 | 16.8557 | 29.015 | 31.1122 | |
|
| 2.0571 | 3.0 | 1077 | 1.8391 | 32.99 | 16.716 | 28.8118 | 30.9178 | |
|
| 2.0001 | 4.0 | 1436 | 1.8357 | 33.0543 | 16.6731 | 28.8375 | 30.9604 | |
|
| 1.9609 | 5.0 | 1795 | 1.8437 | 33.1019 | 16.7576 | 28.8669 | 31.001 | |
|
| 1.925 | 6.0 | 2154 | 1.8402 | 33.1388 | 16.7539 | 28.8887 | 31.0262 | |
|
| 1.9036 | 7.0 | 2513 | 1.8423 | 33.1825 | 16.759 | 28.9154 | 31.0656 | |
|
| 1.8821 | 8.0 | 2872 | 1.8436 | 33.2082 | 16.798 | 28.9573 | 31.1044 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.14.0 |
|
- Pytorch 1.5.0 |
|
- Datasets 2.3.2 |
|
- Tokenizers 0.10.3 |
|
|
