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_120-samples_config-1_full
results: []
Llama-31-8B_task-1_120-samples_config-1_full
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: 1.5564
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 |
|---|---|---|---|
| 2.3371 | 1.0 | 11 | 2.2386 |
| 1.7745 | 2.0 | 22 | 1.7577 |
| 1.2294 | 3.0 | 33 | 1.1298 |
| 0.9781 | 4.0 | 44 | 0.9825 |
| 0.8705 | 5.0 | 55 | 0.9252 |
| 0.8269 | 6.0 | 66 | 0.8844 |
| 0.6627 | 7.0 | 77 | 0.8656 |
| 0.6053 | 8.0 | 88 | 0.8689 |
| 0.5258 | 9.0 | 99 | 0.9307 |
| 0.3668 | 10.0 | 110 | 1.0742 |
| 0.248 | 11.0 | 121 | 1.2238 |
| 0.2039 | 12.0 | 132 | 1.3416 |
| 0.1357 | 13.0 | 143 | 1.4583 |
| 0.1016 | 14.0 | 154 | 1.5564 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1