oh-mistral-bs4096_lr5.00E-06_schedulercosine_with_min_lr_warmup1.00E-01_minlr5.00E-07

This model is a fine-tuned version of mistralai/Mistral-7B-v0.3 on the mlfoundations-dev/oh-dcft-v3.1-gpt-4o-mini dataset.

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-06
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 256
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 4096
  • total_eval_batch_size: 2048
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine_with_min_lr
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 3.0

Training results

Framework versions

  • Transformers 4.46.1
  • Pytorch 2.5.0a0+b465a5843b.nv24.09
  • Datasets 3.0.2
  • Tokenizers 0.20.3
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