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---
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
|