llama2-7b_sft_0.1_ratio_alpaca_gpt4_proj_by_comprehensive_ntrain_1890
This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on the 0.1_ratio_alpaca_gpt4_proj_by_comprehensive_ntrain_1890 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 3.0
Training results
Framework versions
- Transformers 4.46.1
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.20.3
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Model tree for Xinging/llama2-7b_sft_0.1_ratio_alpaca_gpt4_proj_by_comprehensive_ntrain_1890_default
Base model
meta-llama/Llama-2-7b-hf