distilbert-fa-zwnj-base-MLM-pquad

This model is pretained only on the PQuAD dataset. for educational purposes only.

Tokenizer and base model configs are from HooshvareLab/distilbert-fa-zwnj-base on the generator dataset.

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: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 256
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 1
  • mixed_precision_training: Native AMP

Training results

TrainOutput(global_step=31, training_loss=10.31849128969254, metrics={'train_runtime': 42.7618, 'train_samples_per_second': 188.369, 'train_steps_per_second': 0.725, 'total_flos': 263071290359808.0, 'train_loss': 10.31849128969254, 'epoch': 0.98})

Framework versions

  • Transformers 4.26.1
  • Pytorch 1.13.1+cu116
  • Datasets 2.9.0
  • Tokenizers 0.13.2
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