metadata

language:
  - en
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: add_BERT_no_pretrain_rte
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE RTE
          type: glue
          config: rte
          split: validation
          args: rte
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.5270758122743683

add_BERT_no_pretrain_rte

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

Loss: 0.6942
Accuracy: 0.5271

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: 4e-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
0.7731	1.0	20	0.6942	0.5271
0.709	2.0	40	0.7189	0.4729
0.7188	3.0	60	0.6948	0.4729
0.7007	4.0	80	0.6980	0.4729
0.7048	5.0	100	0.7018	0.5271
0.7065	6.0	120	0.7269	0.4729

Framework versions

Transformers 4.30.2
Pytorch 1.14.0a0+410ce96
Datasets 2.12.0
Tokenizers 0.13.3