|
--- |
|
license: apache-2.0 |
|
tags: |
|
- text-classification |
|
- generated_from_trainer |
|
datasets: |
|
- glue |
|
metrics: |
|
- accuracy |
|
- f1 |
|
widget: |
|
- text: ["Yucaipa owned Dominick 's before selling the chain to Safeway in 1998 for $ 2.5 billion.", |
|
"Yucaipa bought Dominick's in 1995 for $ 693 million and sold it to Safeway for $ 1.8 billion in 1998."] |
|
example_title: Not Equivalent |
|
- text: ["Revenue in the first quarter of the year dropped 15 percent from the same period a year earlier.", |
|
"With the scandal hanging over Stewart's company revenue the first quarter of the year dropped 15 percent from the same period a year earlier."] |
|
example_title: Equivalent |
|
model-index: |
|
- name: platzi |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: datasetX |
|
type: glue |
|
config: mrpc |
|
split: validation |
|
args: mrpc |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.8259803921568627 |
|
- name: F1 |
|
type: f1 |
|
value: 0.8657844990548204 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# platzi |
|
|
|
This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the datasetX dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.4514 |
|
- Accuracy: 0.8260 |
|
- F1: 0.8658 |
|
|
|
## 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: 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: 3 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
|
| 0.5383 | 1.09 | 500 | 0.4514 | 0.8260 | 0.8658 | |
|
| 0.3727 | 2.18 | 1000 | 0.4630 | 0.8333 | 0.8764 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.27.1 |
|
- Pytorch 1.13.1+cu116 |
|
- Datasets 2.10.1 |
|
- Tokenizers 0.13.2 |
|
|
