metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
model_index:
  - name: finetuned-bert
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: glue
          type: glue
          args: mrpc
        metric:
          name: F1
          type: f1
          value: 0.9125214408233276

finetuned-bert

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: 0.3916
Accuracy: 0.875
F1: 0.9125

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
0.581	1.0	230	0.4086	0.8260	0.8711
0.366	2.0	460	0.3758	0.8480	0.8963
0.2328	3.0	690	0.3916	0.875	0.9125

Framework versions

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