llama_finetune_cs_20
This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.0872
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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.6881 | 1.0 | 150 | 1.6028 |
1.3532 | 2.0 | 300 | 1.6693 |
0.9084 | 3.0 | 450 | 1.8783 |
0.4352 | 4.0 | 600 | 2.0825 |
0.374 | 5.0 | 750 | 2.1988 |
0.2596 | 6.0 | 900 | 2.2869 |
0.2316 | 7.0 | 1050 | 2.3945 |
0.1754 | 8.0 | 1200 | 2.5528 |
0.1698 | 9.0 | 1350 | 2.6226 |
0.1371 | 10.0 | 1500 | 2.5997 |
0.1702 | 11.0 | 1650 | 2.7153 |
0.1391 | 12.0 | 1800 | 2.6888 |
0.1894 | 13.0 | 1950 | 2.7324 |
0.1504 | 14.0 | 2100 | 2.8534 |
0.132 | 15.0 | 2250 | 2.8804 |
0.1585 | 16.0 | 2400 | 2.9148 |
0.1497 | 17.0 | 2550 | 2.9550 |
0.1099 | 18.0 | 2700 | 3.0002 |
0.1321 | 19.0 | 2850 | 3.0532 |
0.11 | 20.0 | 3000 | 3.0872 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.13.1
- Tokenizers 0.14.1
Model tree for brettbbb/llama_finetune_cs_20
Base model
meta-llama/Llama-2-7b-hf