README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
base_model: bert-base-uncased
model-index:
  - name: sequence_classification
    results:
      - task:
          type: text-classification
          name: Text Classification
        dataset:
          name: glue
          type: glue
          args: mrpc
        metrics:
          - type: accuracy
            value: 0.8529411764705882
            name: Accuracy
          - type: f1
            value: 0.8943661971830987
            name: F1

sequence_classification

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

• Loss: 0.7738
• Accuracy: 0.8529
• F1: 0.8944

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: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	459	0.3519	0.8627	0.9
0.4872	2.0	918	0.6387	0.8333	0.8893
0.2488	3.0	1377	0.7738	0.8529	0.8944

Framework versions

• Transformers 4.13.0.dev0
• Pytorch 1.10.0+cu102
• Datasets 1.15.1
• Tokenizers 0.10.3