|
--- |
|
language: |
|
- en |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
widget: |
|
- text: 'simplify: the incident has been the subject of numerous reports as to ethics |
|
in scholarship .' |
|
- text: 'simplify: the historical method comprises the techniques and guidelines by |
|
which historians use primary sources and other evidence to research and then to |
|
write history .' |
|
- text: 'simplify: none of the authors , contributors , sponsors , administrators |
|
, vandals , or anyone else connected with wikipedia , in any way whatsoever , |
|
can be responsible for your use of the information contained in or linked from |
|
these web pages .' |
|
- text: 'simplify: oregano is an indispensable ingredient in greek cuisine .' |
|
inference: |
|
parameters: |
|
temperature: 1.5 |
|
max_length: 256 |
|
do_sample: true |
|
num_beams: 3 |
|
base_model: t5-small |
|
model-index: |
|
- name: t5-small-finetuned-turk-text-simplification |
|
results: [] |
|
--- |
|
|
|
<!-- 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-turk-text-simplification |
|
|
|
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.1001 |
|
- Rouge2 Precision: 0.6825 |
|
- Rouge2 Recall: 0.4542 |
|
- Rouge2 Fmeasure: 0.5221 |
|
|
|
## 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: 5 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | |
|
|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:| |
|
| 0.4318 | 1.0 | 500 | 0.1053 | 0.682 | 0.4533 | 0.5214 | |
|
| 0.0977 | 2.0 | 1000 | 0.1019 | 0.683 | 0.4545 | 0.5225 | |
|
| 0.0938 | 3.0 | 1500 | 0.1010 | 0.6828 | 0.4547 | 0.5226 | |
|
| 0.0916 | 4.0 | 2000 | 0.1003 | 0.6829 | 0.4545 | 0.5225 | |
|
| 0.0906 | 5.0 | 2500 | 0.1001 | 0.6825 | 0.4542 | 0.5221 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.21.3 |
|
- Pytorch 1.12.1+cu113 |
|
- Datasets 2.4.0 |
|
- Tokenizers 0.12.1 |
|
|
