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_60-samples_config-1_auto
results: []
Llama-31-8B_task-3_60-samples_config-1_auto
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: 0.6328
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 |
|---|---|---|---|
| 2.1804 | 0.8696 | 5 | 2.1300 |
| 1.7781 | 1.9130 | 11 | 1.3089 |
| 0.7143 | 2.9565 | 17 | 0.5687 |
| 0.3741 | 4.0 | 23 | 0.4144 |
| 0.2554 | 4.8696 | 28 | 0.3896 |
| 0.2567 | 5.9130 | 34 | 0.3594 |
| 0.2394 | 6.9565 | 40 | 0.3500 |
| 0.3262 | 8.0 | 46 | 0.3681 |
| 0.204 | 8.8696 | 51 | 0.4215 |
| 0.1772 | 9.9130 | 57 | 0.4067 |
| 0.1163 | 10.9565 | 63 | 0.4379 |
| 0.062 | 12.0 | 69 | 0.5497 |
| 0.0248 | 12.8696 | 74 | 0.6054 |
| 0.0184 | 13.9130 | 80 | 0.6328 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.1.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1