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_auto
results: []
Llama-31-8B_task-1_120-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: 1.3713
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 |
---|---|---|---|
2.1444 | 1.0 | 11 | 1.9951 |
1.5597 | 2.0 | 22 | 1.5854 |
1.1135 | 3.0 | 33 | 1.0142 |
0.8595 | 4.0 | 44 | 0.8794 |
0.7701 | 5.0 | 55 | 0.8356 |
0.7434 | 6.0 | 66 | 0.8024 |
0.6039 | 7.0 | 77 | 0.7895 |
0.5441 | 8.0 | 88 | 0.7838 |
0.4965 | 9.0 | 99 | 0.8283 |
0.353 | 10.0 | 110 | 0.9092 |
0.2505 | 11.0 | 121 | 1.0033 |
0.2204 | 12.0 | 132 | 1.1738 |
0.1355 | 13.0 | 143 | 1.3070 |
0.1041 | 14.0 | 154 | 1.3560 |
0.0759 | 15.0 | 165 | 1.3713 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1