metadata

language:
  - en
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: hBERTv2_new_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: 0.5595667870036101

hBERTv2_new_pretrain_rte

This model is a fine-tuned version of gokuls/bert_12_layer_model_v2_complete_training_new on the GLUE RTE dataset. It achieves the following results on the evaluation set:

Loss: 0.6853
Accuracy: 0.5596

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
0.7512	1.0	20	0.6929	0.4982
0.7204	2.0	40	0.6908	0.5271
0.701	3.0	60	0.6853	0.5596
0.6315	4.0	80	0.7081	0.5632
0.5807	5.0	100	0.8746	0.5343
0.4079	6.0	120	0.8831	0.5632
0.3077	7.0	140	1.0779	0.5487
0.2453	8.0	160	1.1810	0.5415

Framework versions

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