README.md

metadata

license: apache-2.0
tags:
  - text-classification
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
model-index:
  - name: platzi-distilroberta-base-mrpc-glue-will-mendoza
    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: 0.8382352941176471
          - name: F1
            type: f1
            value: 0.8773234200743494

platzi-distilroberta-base-mrpc-glue-will-mendoza

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

• Loss: 0.5374
• Accuracy: 0.8382
• F1: 0.8773

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
0.5458	1.09	500	0.5644	0.8309	0.8832
0.3627	2.18	1000	0.5374	0.8382	0.8773

Framework versions

• Transformers 4.27.4
• Pytorch 2.0.0+cu118
• Datasets 2.11.0
• Tokenizers 0.13.3