README.md

metadata

license: mit
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - matthews_correlation
model_index:
  - name: roberta-base-finetuned-cola
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: glue
          type: glue
          args: cola
        metric:
          name: Matthews Correlation
          type: matthews_correlation
          value: 0.557882735147727

roberta-base-finetuned-cola

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

• Loss: 0.4716
• Matthews Correlation: 0.5579

Model description

More information needed

Intended uses & limitations

from transformers import AutoModelForSequenceClassification
model = AutoModelForSequenceClassification.from_pretrained("jxuhf/roberta-base-finetuned-cola")

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Matthews Correlation
0.4981	1.0	535	0.5162	0.5081
0.314	2.0	1070	0.4716	0.5579

Framework versions

• Transformers 4.9.0
• Pytorch 1.9.0+cu102
• Datasets 1.10.2
• Tokenizers 0.10.3