formalmathatepfl / apertus-cpt-sft-classic

huggingface.co
Total runs: 2
24-hour runs: 0
7-day runs: 1
30-day runs: -6
Model's Last Updated: May 25 2026

Introduction of apertus-cpt-sft-classic

Model Details of apertus-cpt-sft-classic

g-- library_name: transformers license: other base_model: swiss-ai/Apertus-8B-2509 tags: - llama-factory - full - generated_from_trainer model-index: - name: Apertus-no-feedback results: []

Apertus-no-feedback

This model is a fine-tuned version of /mnt/task_runtime/models/Apertus-8B-cpt on the sft dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0877
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: 1e-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • total_train_batch_size: 16
  • total_eval_batch_size: 16
  • 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: 1.0
Training results
Training Loss Epoch Step Validation Loss
0.1169 0.2286 1000 0.1173
0.0975 0.4572 2000 0.0961
0.0889 0.6859 3000 0.0898
0.0887 0.9145 4000 0.0878
Framework versions
  • Transformers 4.57.6
  • Pytorch 2.9.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.22.2

Runs of formalmathatepfl apertus-cpt-sft-classic on huggingface.co

2
Total runs
0
24-hour runs
0
3-day runs
1
7-day runs
-6
30-day runs

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