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--- |
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license: apache-2.0 |
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tags: |
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- text-classification |
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- generated_from_trainer |
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datasets: |
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- glue |
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metrics: |
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- accuracy |
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- f1 |
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widget: |
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- text: ["Jamaica is the place where Usain Bolt was born", "Usain Bolt was born in the island of Jamaica"] |
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example_title: Equivalent |
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- text: ["Jamaica is the place where Usain Bolt was born", "There are many fast runners in Jamaica"] |
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example_title: Not Equivalent |
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model-index: |
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- name: platzi-distilroberta-base-mrpc-glue |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: glue |
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type: glue |
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config: mrpc |
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split: train |
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args: mrpc |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7843137254901961 |
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- name: F1 |
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type: f1 |
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value: 0.8287937743190662 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# platzi-distilroberta-base-mrpc-glue |
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This model is a fine-tuned version of [distilroberta-base](https://huggingface.co/distilroberta-base) on the glue and the mrpc datasets. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5320 |
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- Accuracy: 0.7843 |
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- F1: 0.8288 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 0.5381 | 1.09 | 500 | 0.5320 | 0.7843 | 0.8288 | |
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| 0.3849 | 2.18 | 1000 | 0.5543 | 0.8431 | 0.8869 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu116 |
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- Datasets 2.8.0 |
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- Tokenizers 0.13.2 |
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