sft-metamath-mistral-7b-vi-v1

This model is a fine-tuned version of hllj/meta-math-mistral-vi-math on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4947

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: 5e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.05
  • num_epochs: 2
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
0.3128 0.26 500 0.5093
0.2751 1.07 1000 0.4884
0.2585 1.33 1500 0.4943

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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