README.md

metadata

tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
model-index:
  - name: ibert-roberta-base-finetuned-mrpc
    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: 0.8578431372549019
          - name: F1
            type: f1
            value: 0.8953068592057761

ibert-roberta-base-finetuned-mrpc

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

• Loss: 0.3775
• Accuracy: 0.8578
• F1: 0.8953

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: 2e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 24
• 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
No log	1.0	115	0.4043	0.8309	0.8821
No log	2.0	230	0.3885	0.8456	0.8927
No log	3.0	345	0.3775	0.8578	0.8953

Framework versions

• Transformers 4.28.0
• Pytorch 2.0.1+cu118
• Datasets 2.14.5
• Tokenizers 0.13.3