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formalmathatepfl/
Apertus-8B-cpt

Name: Apertus-8B-cpt
Availability: InStock

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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

formalmathatepfl/Apertus-8B-cpt

Apertus-8B-cpt

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

formalmathatepfl/
Apertus-8B-cpt