llama_finetune_cs_20_cot
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: 3.3122
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 |
---|---|---|---|
1.5397 | 1.0 | 150 | 1.4682 |
1.2842 | 2.0 | 300 | 1.5033 |
1.0418 | 3.0 | 450 | 1.7145 |
0.3202 | 4.0 | 600 | 1.9554 |
0.3109 | 5.0 | 750 | 2.2233 |
0.3597 | 6.0 | 900 | 2.4190 |
0.1135 | 7.0 | 1050 | 2.4910 |
0.0863 | 8.0 | 1200 | 2.5746 |
0.1082 | 9.0 | 1350 | 2.6889 |
0.0757 | 10.0 | 1500 | 2.7235 |
0.0818 | 11.0 | 1650 | 2.8289 |
0.0698 | 12.0 | 1800 | 2.8434 |
0.0714 | 13.0 | 1950 | 2.7956 |
0.0779 | 14.0 | 2100 | 2.9733 |
0.067 | 15.0 | 2250 | 3.0476 |
0.065 | 16.0 | 2400 | 3.1342 |
0.067 | 17.0 | 2550 | 3.1901 |
0.0777 | 18.0 | 2700 | 3.2490 |
0.0647 | 19.0 | 2850 | 3.3113 |
0.0661 | 20.0 | 3000 | 3.3122 |
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_cot
Base model
meta-llama/Llama-2-7b-hf