metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
model_index:
  - name: finetuned-bert-mrpc
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: glue
          type: glue
          args: mrpc
        metric:
          name: F1
          type: f1
          value: 0.8791946308724832

finetuned-bert-mrpc

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

Loss: 0.4917
Accuracy: 0.8235
F1: 0.8792

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: 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: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.5382	1.0	230	0.4008	0.8456	0.8893
0.3208	2.0	460	0.4182	0.8309	0.8844
0.1587	3.0	690	0.4917	0.8235	0.8792

Framework versions

Transformers 4.9.0.dev0
Pytorch 1.8.1+cu111
Datasets 1.8.1.dev0
Tokenizers 0.10.1