metadata

language:
  - en
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
  - f1
model-index:
  - name: mobilebert_sa_GLUE_Experiment_data_aug_mrpc
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE MRPC
          type: glue
          args: mrpc
        metrics:
          - name: Accuracy
            type: accuracy
            value: 1
          - name: F1
            type: f1
            value: 1

mobilebert_sa_GLUE_Experiment_data_aug_mrpc

This model is a fine-tuned version of google/mobilebert-uncased on the GLUE MRPC dataset. It achieves the following results on the evaluation set:

Loss: 0.0000
Accuracy: 1.0
F1: 1.0
Combined Score: 1.0

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: 128
eval_batch_size: 128
seed: 10
distributed_type: multi-GPU
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Combined Score
0.1838	1.0	1959	0.0138	0.9951	0.9964	0.9958
0.0406	2.0	3918	0.0055	1.0	1.0	1.0
0.0267	3.0	5877	0.0129	0.9975	0.9982	0.9979
0.0151	4.0	7836	0.0004	1.0	1.0	1.0
0.0108	5.0	9795	0.0104	0.9975	0.9982	0.9979
0.0075	6.0	11754	0.0000	1.0	1.0	1.0
0.0059	7.0	13713	0.0005	1.0	1.0	1.0
0.0047	8.0	15672	0.0000	1.0	1.0	1.0
0.0033	9.0	17631	0.0001	1.0	1.0	1.0
0.0031	10.0	19590	0.0000	1.0	1.0	1.0
0.0025	11.0	21549	0.0000	1.0	1.0	1.0
0.0019	12.0	23508	0.0000	1.0	1.0	1.0
0.0019	13.0	25467	0.0000	1.0	1.0	1.0
0.0014	14.0	27426	0.0000	1.0	1.0	1.0
0.001	15.0	29385	0.0000	1.0	1.0	1.0
0.001	16.0	31344	0.0000	1.0	1.0	1.0
0.0009	17.0	33303	0.0000	1.0	1.0	1.0
0.0009	18.0	35262	0.0000	1.0	1.0	1.0
0.0006	19.0	37221	0.0000	1.0	1.0	1.0
0.0006	20.0	39180	0.0000	1.0	1.0	1.0
0.0003	21.0	41139	0.0000	1.0	1.0	1.0
0.0003	22.0	43098	0.0000	1.0	1.0	1.0
0.0005	23.0	45057	0.0000	1.0	1.0	1.0

Framework versions

Transformers 4.26.0
Pytorch 1.14.0a0+410ce96
Datasets 2.9.0
Tokenizers 0.13.2