rishavranaut / Mistral_Task2_semantic_pred

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Introduction of Mistral_Task2_semantic_pred

Model Details of Mistral_Task2_semantic_pred

Mistral_Task2_semantic_pred

This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.0200
  • Accuracy: 0.7414
  • Precision: 0.6613
  • Recall: 0.9749
  • F1 score: 0.7880
Model description

More information needed

Intended uses & limitations

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Training and evaluation data

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Training procedure
Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0001
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 4
Training results
Training Loss Epoch Step Accuracy F1 score Precision Recall Validation Loss
0.8426 0.5208 200 0.7824 0.7958 0.7406 0.8600 0.6397
0.6067 1.0417 400 0.6599 0.7353 0.5967 0.9577 0.9629
0.3511 1.5625 600 0.7922 0.8151 0.7262 0.9287 0.5420
0.3361 2.0833 800 0.9585 0.6769 0.6074 0.9749 0.7485
0.2423 2.6042 1000 0.4802 0.8339 0.7728 0.9392 0.8479
0.2082 3.125 1200 0.6629 0.7961 0.7181 0.9657 0.8237
0.1397 3.6458 1400 1.0200 0.7414 0.6613 0.9749 0.7880
Framework versions
  • PEFT 0.12.0
  • Transformers 4.44.2
  • Pytorch 2.4.0+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1

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