|
--- |
|
license: llama3 |
|
library_name: peft |
|
tags: |
|
- alignment-handbook |
|
- trl |
|
- sft |
|
- generated_from_trainer |
|
base_model: meta-llama/Meta-Llama-3-8B |
|
datasets: |
|
- yihanwang617/ultrachat_200k_processed_indicator_0.6_4k |
|
model-index: |
|
- name: llama-3-qlora-ultrachat-200k-processed-indicator-0.6 |
|
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. --> |
|
|
|
# llama-3-qlora-ultrachat-200k-processed-indicator-0.6 |
|
|
|
This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the yihanwang617/ultrachat_200k_processed_indicator_0.6_4k dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.0200 |
|
|
|
## 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 | |
|
|:-------------:|:------:|:----:|:---------------:| |
|
| 1.0614 | 0.0616 | 200 | 1.0632 | |
|
| 1.0689 | 0.1232 | 400 | 1.0476 | |
|
| 1.0053 | 0.1847 | 600 | 1.0413 | |
|
| 1.0446 | 0.2463 | 800 | 1.0366 | |
|
| 1.0091 | 0.3079 | 1000 | 1.0336 | |
|
| 1.0093 | 0.3695 | 1200 | 1.0310 | |
|
| 1.0086 | 0.4311 | 1400 | 1.0291 | |
|
| 1.0362 | 0.4926 | 1600 | 1.0270 | |
|
| 1.0155 | 0.5542 | 1800 | 1.0256 | |
|
| 1.0138 | 0.6158 | 2000 | 1.0240 | |
|
| 1.0392 | 0.6774 | 2200 | 1.0226 | |
|
| 1.0079 | 0.7389 | 2400 | 1.0216 | |
|
| 1.0139 | 0.8005 | 2600 | 1.0208 | |
|
| 0.9857 | 0.8621 | 2800 | 1.0204 | |
|
| 1.0258 | 0.9237 | 3000 | 1.0201 | |
|
| 1.0147 | 0.9853 | 3200 | 1.0200 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.12.0 |
|
- Transformers 4.40.1 |
|
- Pytorch 2.4.0+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
