formalmathatepfl / Apertus-8B-cpt

huggingface.co
Total runs: 8
24-hour runs: 0
7-day runs: 1
30-day runs: 1
Model's Last Updated: May 24 2026
text-generation

Introduction of Apertus-8B-cpt

Model Details of Apertus-8B-cpt

Apertus-8B-cpt

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

  • Loss: 0.9989
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: 3e-06
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • total_train_batch_size: 32
  • total_eval_batch_size: 32
  • 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: cosine
  • lr_scheduler_warmup_ratio: 0.03
  • num_epochs: 2.0
Training results
Training Loss Epoch Step Validation Loss
1.2574 0.1311 100 1.2728
1.1402 0.2621 200 1.1717
1.1055 0.3932 300 1.1226
1.0727 0.5242 400 1.0898
1.0481 0.6553 500 1.0660
1.0351 0.7864 600 1.0474
0.977 0.9174 700 1.0336
0.9933 1.0485 800 1.0230
0.9646 1.1796 900 1.0147
0.945 1.3106 1000 1.0083
1.0034 1.4417 1100 1.0039
0.9788 1.5727 1200 1.0012
0.9938 1.7038 1300 0.9997
1.007 1.8349 1400 0.9991
1.0129 1.9659 1500 0.9989
Framework versions
  • Transformers 4.57.6
  • Pytorch 2.9.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.22.2

Runs of formalmathatepfl Apertus-8B-cpt on huggingface.co

8
Total runs
0
24-hour runs
0
3-day runs
1
7-day runs
1
30-day runs

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Apertus-8B-cpt huggingface.co

Apertus-8B-cpt huggingface.co is an AI model on huggingface.co that provides Apertus-8B-cpt's model effect (), which can be used instantly with this formalmathatepfl Apertus-8B-cpt model. huggingface.co supports a free trial of the Apertus-8B-cpt model, and also provides paid use of the Apertus-8B-cpt. Support call Apertus-8B-cpt model through api, including Node.js, Python, http.

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Apertus-8B-cpt install

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