metadata

language:
  - en
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - matthews_correlation
  - accuracy
model-index:
  - name: sa_BERT_no_pretrain_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
          - name: Accuracy
            type: accuracy
            value: 0.6912751793861389

sa_BERT_no_pretrain_cola

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

Loss: 0.6180
Matthews Correlation: 0.0
Accuracy: 0.6913

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: 0.0005
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
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.8826	1.0	67	0.6624	0.6913
0.616	2.0	134	0.6358	0.6913
0.6134	3.0	201	0.6195	0.6913
0.6139	4.0	268	0.6285	0.6913
0.6117	5.0	335	0.6180	0.6913
0.6099	6.0	402	0.6183	0.6913
0.6113	7.0	469	0.6232	0.6913
0.6135	8.0	536	0.6182	0.6913
0.6094	9.0	603	0.6221	0.6913
0.6096	10.0	670	0.6310	0.6913

Framework versions

Transformers 4.29.2
Pytorch 1.14.0a0+410ce96
Datasets 2.12.0
Tokenizers 0.13.3