metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
model-index:
  - name: platzi-distilroberta-base-mrpc-glue-Jonathan-Castillo
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: glue
          type: glue
          config: mrpc
          split: validation
          args: mrpc
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8455882352941176
          - name: F1
            type: f1
            value: 0.891566265060241

platzi-distilroberta-base-mrpc-glue-Jonathan-Castillo

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

Loss: 1.2969
Accuracy: 0.8456
F1: 0.8916

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: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.5304	1.09	500	0.7888	0.7966	0.8659
0.3762	2.18	1000	0.6592	0.8382	0.8850
0.2122	3.27	1500	0.9311	0.8333	0.8828
0.1345	4.36	2000	0.9803	0.8505	0.8968
0.066	5.45	2500	1.0714	0.8578	0.8968
0.0306	6.54	3000	1.2510	0.8456	0.8923
0.0198	7.63	3500	1.2969	0.8456	0.8916

Framework versions

Transformers 4.28.1
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.3