|
--- |
|
base_model: meta-llama/Meta-Llama-3-8B |
|
library_name: peft |
|
license: llama3 |
|
tags: |
|
- trl |
|
- sft |
|
- generated_from_trainer |
|
model-index: |
|
- name: llama3-8B-EIP-8bit-lora |
|
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. --> |
|
|
|
# llama3-8B-EIP-8bit-lora |
|
|
|
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.5218 |
|
|
|
## 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 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 1 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:------:|:----:|:---------------:| |
|
| 2.4743 | 0.0433 | 100 | 1.7806 | |
|
| 1.6838 | 0.0866 | 200 | 1.6540 | |
|
| 1.6055 | 0.1299 | 300 | 1.6010 | |
|
| 1.5809 | 0.1732 | 400 | 1.5646 | |
|
| 1.5472 | 0.2165 | 500 | 1.5350 | |
|
| 1.5206 | 0.2599 | 600 | 1.5218 | |
|
| 1.5358 | 0.3032 | 700 | 1.5218 | |
|
| 1.5102 | 0.3465 | 800 | 1.5218 | |
|
| 1.552 | 0.3898 | 900 | 1.5218 | |
|
| 1.5354 | 0.4331 | 1000 | 1.5218 | |
|
| 1.5269 | 0.4764 | 1100 | 1.5218 | |
|
| 1.5202 | 0.5197 | 1200 | 1.5218 | |
|
| 1.5434 | 0.5630 | 1300 | 1.5218 | |
|
| 1.5325 | 0.6063 | 1400 | 1.5218 | |
|
| 1.5307 | 0.6496 | 1500 | 1.5218 | |
|
| 1.5287 | 0.6929 | 1600 | 1.5218 | |
|
| 1.5277 | 0.7362 | 1700 | 1.5218 | |
|
| 1.5176 | 0.7796 | 1800 | 1.5218 | |
|
| 1.5268 | 0.8229 | 1900 | 1.5218 | |
|
| 1.5306 | 0.8662 | 2000 | 1.5218 | |
|
| 1.5309 | 0.9095 | 2100 | 1.5218 | |
|
| 1.5484 | 0.9528 | 2200 | 1.5218 | |
|
| 1.51 | 0.9961 | 2300 | 1.5218 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.11.1 |
|
- Transformers 4.42.3 |
|
- Pytorch 2.1.0a0+4136153 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
