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-3_180-samples_config-1
results: []
Llama-31-8B_task-3_180-samples_config-1
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: 0.8358
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 |
|---|---|---|---|
| 1.9354 | 1.0 | 17 | 1.7708 |
| 0.6268 | 2.0 | 34 | 0.6221 |
| 0.3923 | 3.0 | 51 | 0.5086 |
| 0.2943 | 4.0 | 68 | 0.4581 |
| 0.3006 | 5.0 | 85 | 0.4390 |
| 0.3831 | 6.0 | 102 | 0.4377 |
| 0.2878 | 7.0 | 119 | 0.4980 |
| 0.1028 | 8.0 | 136 | 0.6312 |
| 0.0608 | 9.0 | 153 | 0.6599 |
| 0.0272 | 10.0 | 170 | 0.7522 |
| 0.0172 | 11.0 | 187 | 0.8401 |
| 0.0086 | 12.0 | 204 | 0.8499 |
| 0.0078 | 13.0 | 221 | 0.8358 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1