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_60-samples_config-2_full
results: []
Llama-31-8B_task-1_60-samples_config-2_full
This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9806
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: 16
- total_train_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: 50
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.5391 | 0.6957 | 2 | 2.3916 |
| 2.4703 | 1.7391 | 5 | 2.2074 |
| 2.1328 | 2.7826 | 8 | 1.9537 |
| 1.9709 | 3.8261 | 11 | 1.6769 |
| 1.5704 | 4.8696 | 14 | 1.3962 |
| 1.3765 | 5.9130 | 17 | 1.1358 |
| 1.0594 | 6.9565 | 20 | 1.0275 |
| 0.9969 | 8.0 | 23 | 0.9877 |
| 0.9485 | 8.6957 | 25 | 0.9700 |
| 0.8932 | 9.7391 | 28 | 0.9503 |
| 0.8815 | 10.7826 | 31 | 0.9331 |
| 0.8229 | 11.8261 | 34 | 0.9216 |
| 0.8136 | 12.8696 | 37 | 0.9111 |
| 0.7507 | 13.9130 | 40 | 0.9021 |
| 0.7373 | 14.9565 | 43 | 0.8982 |
| 0.6959 | 16.0 | 46 | 0.9020 |
| 0.6651 | 16.6957 | 48 | 0.9060 |
| 0.6589 | 17.7391 | 51 | 0.9119 |
| 0.5782 | 18.7826 | 54 | 0.9264 |
| 0.585 | 19.8261 | 57 | 0.9372 |
| 0.511 | 20.8696 | 60 | 0.9604 |
| 0.4767 | 21.9130 | 63 | 0.9806 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1