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baby-python-mistral-1L-tiny-base - GGUF
- Model creator: https://huggingface.co/nilq/
- Original model: https://huggingface.co/nilq/baby-python-mistral-1L-tiny-base/
Original model description:
tags: - generated_from_trainer datasets: - nilq/baby-python metrics: - accuracy model-index: - name: baby-python-mistral-1L-tiny-base results: - task: name: Causal Language Modeling type: text-generation dataset: name: nilq/baby-python type: nilq/baby-python metrics: - name: Accuracy type: accuracy value: 0.41903868169401487
baby-python-mistral-1L-tiny-base
This model is trained on the nilq/baby-python dataset. It is the base model in the paper Tracking Universal Features Through Fine-Tuning and Model Merging. It achieves the following results on the evaluation set:
- Loss: 3.1027
- Accuracy: 0.4190
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: 0.0006
- train_batch_size: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 3.0
Training results
Framework versions
- Transformers 4.38.1
- Pytorch 2.2.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
- Downloads last month
- 67
Hardware compatibility
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