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cvgpt-ft

This model is a fine-tuned version of TheBloke/Mistral-7B-Instruct-v0.2-GPTQ on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.7107

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: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 2
  • num_epochs: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
0.941 1.0 1 1.9446
0.8845 2.0 2 1.9283
0.9258 3.0 3 1.8865
0.916 4.0 4 1.8419
0.9012 5.0 5 1.8004
0.7434 6.0 6 1.7642
0.822 7.0 7 1.7409
0.7946 8.0 8 1.7253
0.7461 9.0 9 1.7156
0.7523 10.0 10 1.7107

Framework versions

  • PEFT 0.10.0
  • Transformers 4.40.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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