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Librarian Bot: Add base_model information to model (#1)
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metadata
license: apache-2.0
tags:
  - text-classification
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
base_model: distilroberta-base
model-index:
  - name: platzi-distilroberta-base-mrpc-glue-luigitercero
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: datasetX
          type: glue
          config: mrpc
          split: validation
          args: mrpc
        metrics:
          - type: accuracy
            value: 0.8431372549019608
            name: Accuracy
          - type: f1
            value: 0.8836363636363636
            name: F1

platzi-distilroberta-base-mrpc-glue-luigitercero

This model is a fine-tuned version of distilroberta-base on the datasetX dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6591
  • Accuracy: 0.8431
  • F1: 0.8836

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
0.1853 1.09 500 0.6591 0.8431 0.8836
0.1812 2.18 1000 0.6591 0.8431 0.8836

Framework versions

  • Transformers 4.26.1
  • Pytorch 1.13.1+cu116
  • Datasets 2.9.0
  • Tokenizers 0.13.2