Llama-3.2-1B-Instruct-LoRA-v1
This model is a fine-tuned version of blattimer/Llama-3.2-1B-Instruct 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 1
Training results
Framework versions
- PEFT 0.14.0
- Transformers 4.49.0
- Pytorch 2.4.0+cu121
- Datasets 3.3.2
- Tokenizers 0.21.0
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Model tree for blattimer/Llama-3.2-1B-Instruct-LoRA-v1
Base model
meta-llama/Llama-3.2-1B-Instruct
Finetuned
blattimer/Llama-3.2-1B-Instruct