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hBERTv2_new_pretrain_w_init__rte

This model is a fine-tuned version of gokuls/bert_12_layer_model_v2_complete_training_new_wt_init on the GLUE RTE dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6913
  • Accuracy: 0.5523

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
0.7456 1.0 20 0.6913 0.5523
0.7047 2.0 40 0.7129 0.5271
0.6813 3.0 60 0.7151 0.5307
0.6329 4.0 80 0.7451 0.5235
0.5965 5.0 100 0.7838 0.5307
0.5075 6.0 120 0.8684 0.5487

Framework versions

  • Transformers 4.29.2
  • Pytorch 1.14.0a0+410ce96
  • Datasets 2.12.0
  • Tokenizers 0.13.3
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Inference API
This model can be loaded on Inference API (serverless).

Dataset used to train gokuls/hBERTv2_new_pretrain_w_init__rte

Evaluation results