metadata
base_model: meta-llama/Meta-Llama-3-8B
library_name: peft
license: llama3
tags:
- trl
- sft
- alignment-handbook
- generated_from_trainer
model-index:
- name: llama-3-qlora-ultrachat-200k-processed-indicator-0.6
results: []
llama-3-qlora-ultrachat-200k-processed-indicator-0.6
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B on an unknown 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