metadata
base_model: meta-llama/Meta-Llama-3-8B
datasets:
- yihanwang617/WizardLM_70k_processed_indicator_4k
library_name: peft
license: llama3
tags:
- alignment-handbook
- trl
- sft
- generated_from_trainer
model-index:
- name: llama-3-qlora-wizard-processed-indicator-0.6
results: []
llama-3-qlora-wizard-processed-indicator-0.6
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on the yihanwang617/WizardLM_70k_processed_indicator_4k dataset. It achieves the following results on the evaluation set:
- Loss: 0.6735
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: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.7109 | 0.1842 | 200 | 0.7065 |
| 0.7185 | 0.3683 | 400 | 0.6904 |
| 0.7062 | 0.5525 | 600 | 0.6819 |
| 0.6629 | 0.7366 | 800 | 0.6758 |
| 0.6769 | 0.9208 | 1000 | 0.6736 |
Framework versions
- PEFT 0.12.0
- Transformers 4.40.1
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1