metadata
base_model: meta-llama/Llama-2-7b-hf
library_name: peft
license: llama2
tags:
- generated_from_trainer
model-index:
- name: llama2-7b-qlora-finetuned_1
results: []
llama2-7b-qlora-finetuned_1
This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4910
- Model Preparation Time: 0.0048
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: 4
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Use 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: 100
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time |
|---|---|---|---|---|
| 8.4619 | 0.1669 | 100 | 0.5918 | 0.0048 |
| 0.5531 | 0.3339 | 200 | 0.5314 | 0.0048 |
| 0.5311 | 0.5008 | 300 | 0.5164 | 0.0048 |
| 0.5179 | 0.6677 | 400 | 0.5114 | 0.0048 |
| 0.5168 | 0.8346 | 500 | 0.5072 | 0.0048 |
| 0.5124 | 1.0016 | 600 | 0.5034 | 0.0048 |
| 0.5053 | 1.1685 | 700 | 0.5003 | 0.0048 |
| 0.5047 | 1.3354 | 800 | 0.5001 | 0.0048 |
| 0.5008 | 1.5023 | 900 | 0.4967 | 0.0048 |
| 0.4985 | 1.6693 | 1000 | 0.4969 | 0.0048 |
| 0.4998 | 1.8362 | 1100 | 0.4941 | 0.0048 |
| 0.4987 | 2.0031 | 1200 | 0.4978 | 0.0048 |
| 0.4939 | 2.1701 | 1300 | 0.4933 | 0.0048 |
| 0.4907 | 2.3370 | 1400 | 0.4923 | 0.0048 |
| 0.4947 | 2.5039 | 1500 | 0.4910 | 0.0048 |
| 0.4896 | 2.6708 | 1600 | 0.4901 | 0.0048 |
| 0.4923 | 2.8378 | 1700 | 0.4896 | 0.0048 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0