llama_finetune_arc_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: 2.8405
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 |
---|---|---|---|
1.4833 | 1.0 | 150 | 1.2465 |
0.7985 | 2.0 | 300 | 1.3109 |
0.7027 | 3.0 | 450 | 1.5734 |
0.2639 | 4.0 | 600 | 1.8512 |
0.1926 | 5.0 | 750 | 1.8805 |
0.1698 | 6.0 | 900 | 2.0632 |
0.1776 | 7.0 | 1050 | 2.1963 |
0.1594 | 8.0 | 1200 | 2.2222 |
0.1209 | 9.0 | 1350 | 2.1946 |
0.1142 | 10.0 | 1500 | 2.3561 |
0.1039 | 11.0 | 1650 | 2.4107 |
0.1015 | 12.0 | 1800 | 2.5198 |
0.1209 | 13.0 | 1950 | 2.4374 |
0.1324 | 14.0 | 2100 | 2.5536 |
0.1252 | 15.0 | 2250 | 2.6239 |
0.0989 | 16.0 | 2400 | 2.6389 |
0.139 | 17.0 | 2550 | 2.7198 |
0.1077 | 18.0 | 2700 | 2.7891 |
0.084 | 19.0 | 2850 | 2.8138 |
0.0765 | 20.0 | 3000 | 2.8405 |
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
Base model
meta-llama/Llama-2-7b-hf