metadata

language:
  - en
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
model-index:
  - name: bert-large-cased-finetuned-mrpc
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE MRPC
          type: glue
          args: mrpc
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.6838235294117647
          - name: F1
            type: f1
            value: 0.8122270742358079

bert-large-cased-finetuned-mrpc

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

Loss: 0.6274
Accuracy: 0.6838
F1: 0.8122
Combined Score: 0.7480

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: 4
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Combined Score
0.6441	1.0	917	0.6370	0.6838	0.8122	0.7480
0.6451	2.0	1834	0.6553	0.6838	0.8122	0.7480
0.6428	3.0	2751	0.6332	0.6838	0.8122	0.7480
0.6476	4.0	3668	0.6248	0.6838	0.8122	0.7480
0.6499	5.0	4585	0.6274	0.6838	0.8122	0.7480

Framework versions

Transformers 4.11.0.dev0
Pytorch 1.9.0
Datasets 1.12.1
Tokenizers 0.10.3