|
--- |
|
base_model: meta-llama/Meta-Llama-3-8B-Instruct |
|
library_name: peft |
|
license: llama3 |
|
tags: |
|
- trl |
|
- sft |
|
- generated_from_trainer |
|
model-index: |
|
- name: llama-qLoRA |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/dhanishetty-personaluse/huggingface/runs/7iegxn0n) |
|
# llama-qLoRA |
|
|
|
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.9017 |
|
|
|
## 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: 5e-05 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- total_train_batch_size: 16 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: inverse_sqrt |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 3 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:------:|:----:|:---------------:| |
|
| 1.1337 | 0.2022 | 100 | 1.1567 | |
|
| 0.9957 | 0.4044 | 200 | 0.9863 | |
|
| 0.9269 | 0.6067 | 300 | 0.9463 | |
|
| 0.944 | 0.8089 | 400 | 0.9343 | |
|
| 0.8779 | 1.0111 | 500 | 0.9271 | |
|
| 0.8902 | 1.2133 | 600 | 0.9218 | |
|
| 0.9149 | 1.4156 | 700 | 0.9156 | |
|
| 0.8801 | 1.6178 | 800 | 0.9126 | |
|
| 0.8752 | 1.8200 | 900 | 0.9093 | |
|
| 0.8477 | 2.0222 | 1000 | 0.9068 | |
|
| 0.8506 | 2.2245 | 1100 | 0.9067 | |
|
| 0.8676 | 2.4267 | 1200 | 0.9048 | |
|
| 0.8504 | 2.6289 | 1300 | 0.9028 | |
|
| 0.8617 | 2.8311 | 1400 | 0.9017 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.11.1 |
|
- Transformers 4.42.4 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
