|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- cnn_dailymail |
|
metrics: |
|
- rouge |
|
base_model: Chikashi/t5-small-finetuned-cnndm2-wikihow2 |
|
model-index: |
|
- name: t5-small-finetuned-cnndm3-wikihow2 |
|
results: |
|
- task: |
|
type: text2text-generation |
|
name: Sequence-to-sequence Language Modeling |
|
dataset: |
|
name: cnn_dailymail |
|
type: cnn_dailymail |
|
args: 3.0.0 |
|
metrics: |
|
- type: rouge |
|
value: 24.6704 |
|
name: Rouge1 |
|
--- |
|
|
|
<!-- 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-cnndm3-wikihow2 |
|
|
|
This model is a fine-tuned version of [Chikashi/t5-small-finetuned-cnndm2-wikihow2](https://huggingface.co/Chikashi/t5-small-finetuned-cnndm2-wikihow2) on the cnn_dailymail dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.6265 |
|
- Rouge1: 24.6704 |
|
- Rouge2: 11.9038 |
|
- Rougel: 20.3622 |
|
- Rougelsum: 23.2612 |
|
- Gen Len: 18.9997 |
|
|
|
## 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: 0.0003 |
|
- train_batch_size: 4 |
|
- eval_batch_size: 4 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 1 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
|
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
|
| 1.8071 | 1.0 | 71779 | 1.6265 | 24.6704 | 11.9038 | 20.3622 | 23.2612 | 18.9997 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.18.0 |
|
- Pytorch 1.10.0+cu111 |
|
- Datasets 2.1.0 |
|
- Tokenizers 0.12.1 |
|
|