metadata

language:
  - en
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: hBERTv2_new_no_pretrain_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: 0.3295362082994304

hBERTv2_new_no_pretrain_mnli

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

Loss: 1.0984
Accuracy: 0.3295

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
1.108	1.0	3068	1.0985	0.3545
1.0988	2.0	6136	1.0986	0.3182
1.0986	3.0	9204	1.0984	0.3274
1.0986	4.0	12272	1.0989	0.3545
1.0986	5.0	15340	1.0984	0.3545
1.0986	6.0	18408	1.0984	0.3274
1.0986	7.0	21476	1.0984	0.3274
1.0986	8.0	24544	1.0985	0.3545
1.0986	9.0	27612	1.0985	0.3545
1.0986	10.0	30680	1.0987	0.3182
1.0986	11.0	33748	1.0989	0.3182

Framework versions

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