llama3.18B-Fine-tunedGOAT
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B on an unknown 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Use paged_adamw_32bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- training_steps: 250
- mixed_precision_training: Native AMP
Training results
Framework versions
- PEFT 0.12.0
- Transformers 4.48.3
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.21.0
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Model tree for worde-byte/llama3.18B-Fine-tunedGOAT
Base model
meta-llama/Llama-3.1-8B