README.md

metadata

base_model: gokuls/HBERTv1_L12_H768_A12_ffn_1
tags:
  - generated_from_trainer
datasets:
  - gokuls/wiki_book_corpus_complete_processed_bert_dataset
metrics:
  - accuracy
model-index:
  - name: HBERTv1_48_L12_H768_A12_ffn_1_KD
    results:
      - task:
          name: Masked Language Modeling
          type: fill-mask
        dataset:
          name: gokuls/wiki_book_corpus_complete_processed_bert_dataset
          type: gokuls/wiki_book_corpus_complete_processed_bert_dataset
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.4616582527830643

HBERTv1_48_L12_H768_A12_ffn_1_KD

This model is a fine-tuned version of gokuls/HBERTv1_L12_H768_A12_ffn_1 on the gokuls/wiki_book_corpus_complete_processed_bert_dataset dataset. It achieves the following results on the evaluation set:

• Loss: 132.3779
• Accuracy: 0.4617

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: 1e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 10
• distributed_type: multi-GPU
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 10000
• num_epochs: 100

Training results

Framework versions

• Transformers 4.35.2
• Pytorch 1.14.0a0+410ce96
• Datasets 2.15.0
• Tokenizers 0.15.0