metadata
library_name: peft
license: llama3.2
base_model: meta-llama/Llama-3.2-1B-Instruct
tags:
- base_model:adapter:meta-llama/Llama-3.2-1B-Instruct
- lora
- transformers
pipeline_tag: text-generation
model-index:
- name: Llama3.2-1B-QLoRA-Explainer
results: []
Llama3.2-1B-QLoRA-Explainer
This model is a fine-tuned version of meta-llama/Llama-3.2-1B-Instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0579
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
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.0652 | 0.3556 | 200 | 0.0650 |
| 0.0626 | 0.7111 | 400 | 0.0615 |
| 0.06 | 1.0658 | 600 | 0.0596 |
| 0.0596 | 1.4213 | 800 | 0.0591 |
| 0.0588 | 1.7769 | 1000 | 0.0587 |
| 0.0582 | 2.1316 | 1200 | 0.0584 |
| 0.0581 | 2.4871 | 1400 | 0.0583 |
| 0.0576 | 2.8427 | 1600 | 0.0579 |
Framework versions
- PEFT 0.17.0
- Transformers 4.55.2
- Pytorch 2.8.0+cu128
- Datasets 4.0.0
- Tokenizers 0.21.4