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Mistral Summarization

This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on the scitldr dataset. It achieves the following results on the evaluation set:

  • Loss: 2.1059

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: 0.0002
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 2
  • num_epochs: 1
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
2.0732 0.1 200 2.1863
2.1324 0.2 400 2.1925
2.103 0.3 600 2.1876
2.0766 0.4 800 2.1737
2.0825 0.5 1000 2.1555
2.0731 0.6 1200 2.1465
2.0819 0.7 1400 2.1355
1.9802 0.8 1600 2.1223
2.0466 0.9 1800 2.1059

Framework versions

  • PEFT 0.9.0
  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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Adapter for

Dataset used to train pkbiswas/Mistral-7B-Summarization-QLoRa