metadata

license: apache-2.0
base_model: distilroberta-base
tags:
  - text-classification
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
widget:
  - text: I like you. I love you
    example_title: Not Equivalent
  - text: I love you so much. I love you
    example_title: Equivalent
model-index:
  - name: distilroberta-base-mrpc-glue
    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: 0.8892617449664431

distilroberta-base-mrpc-glue

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

Loss: 0.4936
Accuracy: 0.8382
F1: 0.8893

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
0.5377	1.09	500	0.4936	0.8382	0.8893
0.3477	2.18	1000	0.6595	0.8407	0.8862

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.15.0
Tokenizers 0.15.0