llama2-hotpot-finetune
This model is a fine-tuned version of NousResearch/Llama-2-7b-hf on the hotpot-qa dataset.
Model description
More information needed
Dataset used
https://huggingface.co./datasets/hotpot_qa
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- training_steps: 100
- mixed_precision_training: Native AMP
Training results
Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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Model tree for journeygenie/llama2-hotpot-finetune
Base model
NousResearch/Llama-2-7b-hf