metadata
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
library_name: peft
license: llama3.1
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Llama-31-8B_task-1_180-samples_config-1_full_auto
results: []
Llama-31-8B_task-1_180-samples_config-1_full_auto
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.3300
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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.9328 | 1.0 | 17 | 1.8837 |
| 1.3207 | 2.0 | 34 | 1.2487 |
| 0.8894 | 3.0 | 51 | 0.9027 |
| 0.8023 | 4.0 | 68 | 0.8472 |
| 0.7382 | 5.0 | 85 | 0.8033 |
| 0.6937 | 6.0 | 102 | 0.7769 |
| 0.6042 | 7.0 | 119 | 0.7946 |
| 0.4994 | 8.0 | 136 | 0.8584 |
| 0.3568 | 9.0 | 153 | 0.9741 |
| 0.2463 | 10.0 | 170 | 1.0730 |
| 0.1823 | 11.0 | 187 | 1.1565 |
| 0.1229 | 12.0 | 204 | 1.2557 |
| 0.1015 | 13.0 | 221 | 1.3300 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1