Mistral-7B-v0.1-IA3-MathReasoning1

This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4240

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: 2
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 8
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 50
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss
1.4834 0.2667 100 0.6361
0.5032 0.5333 200 0.5080
0.4852 0.8 300 0.4864
0.468 1.0667 400 0.4705
0.4525 1.3333 500 0.4573
0.4355 1.6 600 0.4467
0.4218 1.8667 700 0.4381
0.4277 2.1333 800 0.4315
0.4126 2.4 900 0.4269
0.4132 2.6667 1000 0.4240
0.4222 2.9333 1100 0.4228

Framework versions

  • PEFT 0.17.1
  • Transformers 4.56.2
  • Pytorch 2.8.0+cu126
  • Datasets 4.0.0
  • Tokenizers 0.22.1
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Evaluation results