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Model description

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Intended uses & limitations

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Training and evaluation data

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Training procedure

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Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-5
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 5 1.847501 0.260870
1.9354 2.0 10 1.729485 0.333333
1.9354 3.0 15 1.681863 0.391304

Framework versions

  • Transformers 4.33.3
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3
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