metadata

language:
  - en
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: hBERTv1_new_pretrain_w_init__mnli
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE MNLI
          type: glue
          config: mnli
          split: validation_matched
          args: mnli
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.36421887713588286

hBERTv1_new_pretrain_w_init__mnli

This model is a fine-tuned version of gokuls/bert_12_layer_model_v1_complete_training_new_wt_init on the GLUE MNLI dataset. It achieves the following results on the evaluation set:

Loss: 1.0846
Accuracy: 0.3642

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
1.0911	1.0	3068	1.0944	0.3340
1.0984	2.0	6136	1.0967	0.3182
1.0988	3.0	9204	1.0962	0.3545
1.0989	4.0	12272	1.0970	0.3182
1.0986	5.0	15340	1.0896	0.3515
1.0984	6.0	18408	1.0986	0.3545
1.0992	7.0	21476	1.0994	0.3274
1.0993	8.0	24544	1.0999	0.3545
1.099	9.0	27612	1.0965	0.3182
1.0991	10.0	30680	1.1005	0.3182

Framework versions

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