llama_finetune_arc_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: 2.9424
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 |
---|---|---|---|
1.1762 | 1.0 | 150 | 1.1987 |
0.9486 | 2.0 | 300 | 1.2338 |
0.6296 | 3.0 | 450 | 1.4406 |
0.244 | 4.0 | 600 | 1.7124 |
0.2032 | 5.0 | 750 | 1.8587 |
0.1091 | 6.0 | 900 | 2.0025 |
0.1157 | 7.0 | 1050 | 2.0500 |
0.1458 | 8.0 | 1200 | 2.2667 |
0.0639 | 9.0 | 1350 | 2.1986 |
0.0651 | 10.0 | 1500 | 2.3844 |
0.0621 | 11.0 | 1650 | 2.4926 |
0.0474 | 12.0 | 1800 | 2.5012 |
0.0524 | 13.0 | 1950 | 2.6149 |
0.0789 | 14.0 | 2100 | 2.6728 |
0.0428 | 15.0 | 2250 | 2.7003 |
0.0446 | 16.0 | 2400 | 2.7733 |
0.0762 | 17.0 | 2550 | 2.8436 |
0.0535 | 18.0 | 2700 | 2.9111 |
0.04 | 19.0 | 2850 | 2.9168 |
0.0419 | 20.0 | 3000 | 2.9424 |
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_arc_20_cot
Base model
meta-llama/Llama-2-7b-hf