etiennebamas / qwen3-sft-classic-small-data-equal-compute

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Total runs: 75
24-hour runs: 0
7-day runs: -16
30-day runs: -320
Model's Last Updated: September 02 2026
text-generation

Introduction of qwen3-sft-classic-small-data-equal-compute

Model Details of qwen3-sft-classic-small-data-equal-compute

Qwen3-sft-classic-one-shot-equal

This model is a fine-tuned version of formalmathatepfl/qwen3-cpt on the sft 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: 2e-05
  • train_batch_size: 1
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • total_train_batch_size: 8
  • total_eval_batch_size: 64
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.05
  • num_epochs: 2.15
Training results
Framework versions
  • Transformers 4.57.3
  • Pytorch 2.9.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.22.2

Runs of etiennebamas qwen3-sft-classic-small-data-equal-compute on huggingface.co

75
Total runs
0
24-hour runs
-10
3-day runs
-16
7-day runs
-320
30-day runs

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Updated:April 30 2026