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Mistral-7B-Instruct-v0.2-GPTQ_finetune_s1000

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: 0.6456

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
1.2303 0.9829 43 0.8563
0.6964 1.9886 87 0.7045
0.6032 2.9943 131 0.6661
0.558 4.0 175 0.6472
0.5376 4.9829 218 0.6400
0.4962 5.9886 262 0.6360
0.4754 6.9943 306 0.6359
0.4593 8.0 350 0.6393
0.456 8.9829 393 0.6430
0.4305 9.8286 430 0.6456

Framework versions

  • PEFT 0.11.1
  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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