metadata

language:
  - en
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - matthews_correlation
model-index:
  - name: paraphrase-MiniLM-L12-v2-CoLA
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE COLA
          type: glue
          config: cola
          split: validation
          args: cola
        metrics:
          - name: Matthews Correlation
            type: matthews_correlation
            value: 0.5057060886900621
widget:
  - text: The cat sat on the mat.
    example_title: Correct grammatical sentence
  - text: Me and my friend going to the store.
    example_title: Incorrect subject-verb agreement
  - text: I ain't got no money.
    example_title: Incorrect verb conjugation and double negative
  - text: She don't like pizza no more.
    example_title: Incorrect verb conjugation and double negative
  - text: They is arriving tomorrow.
    example_title: Incorrect verb conjugation

paraphrase-MiniLM-L12-v2-CoLA

This model is a fine-tuned version of sentence-transformers/paraphrase-MiniLM-L12-v2 on the GLUE COLA dataset. It achieves the following results on the evaluation set:

Loss: 0.4636
Matthews Correlation: 0.5057

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: 8e-05
train_batch_size: 64
eval_batch_size: 16
seed: 30198
distributed_type: multi-GPU
gradient_accumulation_steps: 2
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.03
num_epochs: 16.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Matthews Correlation
0.5747	1.0	67	0.5394	0.3455
0.5025	2.0	134	0.4999	0.4270
0.3698	3.0	201	0.4636	0.5057
0.2969	4.0	268	0.5309	0.4751
0.2275	5.0	335	0.6238	0.4775
0.1859	6.0	402	0.6315	0.4867
0.1517	7.0	469	0.7783	0.4695
0.1016	8.0	536	0.6762	0.4901
0.1017	9.0	603	0.7412	0.5046
0.0898	10.0	670	0.7719	0.4877
0.0527	11.0	737	0.8627	0.4955
0.0582	12.0	804	0.8986	0.4738
0.074	13.0	871	0.9469	0.4942
0.0508	14.0	938	0.9436	0.4918
0.024	15.0	1005	0.9391	0.4919
0.0458	16.0	1072	0.9375	0.4946

Framework versions

Transformers 4.27.0.dev0
Pytorch 1.13.1+cu117
Datasets 2.8.0
Tokenizers 0.13.1