metadata
library_name: peft
license: llama3.1
base_model: meta-llama/Llama-3.1-8B-Instruct
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: llama-7b-offense
results: []
llama-7b-offense
This model is a fine-tuned version of meta-llama/Llama-3.1-8B-Instruct on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5788
- Accuracy: 0.7709
- F1: 0.5386
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: 0.0002
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 0.9662 | 100 | 0.7477 | 0.6895 | 0.3890 |
| No log | 1.9275 | 200 | 0.6635 | 0.7186 | 0.4739 |
| No log | 2.8889 | 300 | 0.6167 | 0.7430 | 0.5328 |
| No log | 3.8502 | 400 | 0.6212 | 0.7384 | 0.5399 |
| 2.5728 | 4.8116 | 500 | 0.5934 | 0.7558 | 0.5532 |
| 2.5728 | 5.7729 | 600 | 0.5906 | 0.7605 | 0.5231 |
| 2.5728 | 6.7343 | 700 | 0.5838 | 0.7698 | 0.505 |
| 2.5728 | 7.6957 | 800 | 0.5780 | 0.7605 | 0.5381 |
| 2.5728 | 8.6570 | 900 | 0.5799 | 0.7686 | 0.5340 |
| 1.9058 | 9.6184 | 1000 | 0.5788 | 0.7709 | 0.5386 |
Framework versions
- PEFT 0.14.0
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0