README.md

metadata

license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
model-index:
  - name: bert-base-multilingual-cased-mrpc-glue
    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: 0.7769607843137255
          - name: F1
            type: f1
            value: 0.8544

bert-base-multilingual-cased-mrpc-glue

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

• Loss: 0.5550
• Accuracy: 0.7770
• F1: 0.8544

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
0.604	1.09	500	0.5185	0.7426	0.8059
0.4834	2.18	1000	0.5550	0.7770	0.8544

Framework versions

• Transformers 4.31.0
• Pytorch 2.0.1+cu118
• Datasets 2.14.4
• Tokenizers 0.13.3