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metadata
language:
  - en
base_model: gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48
tags:
  - generated_from_trainer
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: hBERTv1_new_pretrain_w_init_48_ver2_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

hBERTv1_new_pretrain_w_init_48_ver2_rte

This model is a fine-tuned version of gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48 on the GLUE RTE dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6919
  • 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: 64
  • eval_batch_size: 64
  • seed: 10
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.7175 1.0 39 0.6919 0.5271
0.7099 2.0 78 0.7006 0.4729
0.7111 3.0 117 0.6927 0.5271
0.7011 4.0 156 0.6976 0.4729
0.7021 5.0 195 0.6955 0.4729
0.6986 6.0 234 0.7078 0.4729

Framework versions

  • Transformers 4.34.0
  • Pytorch 1.14.0a0+410ce96
  • Datasets 2.14.5
  • Tokenizers 0.14.1