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Model: formalmathatepfl/Apertus-8B-finetuned
Source: Original Platform

README.md

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+---
+library_name: transformers
+license: other
+base_model: models/Apertus_CPT_eval
+tags:
+- llama-factory
+- full
+- generated_from_trainer
+model-index:
+- name: finetuning_apertus
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# finetuning_apertus
+
+This model is a fine-tuned version of [models/Apertus_CPT_eval](https://huggingface.co/models/Apertus_CPT_eval) on the finetuning_data 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: 0.0001
+- train_batch_size: 2
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- total_eval_batch_size: 64
+- 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
+- lr_scheduler_warmup_ratio: 0.03
+- num_epochs: 1.0
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.56.2
+- Pytorch 2.9.1+cu128
+- Datasets 3.6.0
+- Tokenizers 0.22.2