Llama-3.1-8B-ceCodeAlpaca-OurInstruct
This model is a fine-tuned version of meta-llama/Llama-3.1-8B on the None 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: 1e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Use adafactor and the args are: No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 2000
Training results
Framework versions
- Transformers 4.53.3
- Pytorch 2.2.0a0+81ea7a4
- Datasets 3.6.0
- Tokenizers 0.21.2
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Model tree for Grogros/Llama-3.1-8B-OurInstruct
Base model
meta-llama/Llama-3.1-8B