mc_cot_16
This model is a fine-tuned version of lmsys/vicuna-7b-v1.5 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.0303
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 |
---|---|---|---|
2.1538 | 1.0 | 4 | 2.1552 |
1.7905 | 2.0 | 8 | 1.9012 |
1.4229 | 3.0 | 12 | 1.7686 |
1.3834 | 4.0 | 16 | 1.7070 |
1.4421 | 5.0 | 20 | 1.7308 |
0.9003 | 6.0 | 24 | 1.7646 |
0.7013 | 7.0 | 28 | 1.9070 |
0.6291 | 8.0 | 32 | 2.0078 |
0.3314 | 9.0 | 36 | 2.2682 |
0.1554 | 10.0 | 40 | 2.3624 |
0.0814 | 11.0 | 44 | 2.6523 |
0.0499 | 12.0 | 48 | 2.7565 |
0.0216 | 13.0 | 52 | 2.8505 |
0.0197 | 14.0 | 56 | 2.9170 |
0.0174 | 15.0 | 60 | 2.9433 |
0.0174 | 16.0 | 64 | 2.9683 |
0.0145 | 17.0 | 68 | 2.9966 |
0.013 | 18.0 | 72 | 3.0193 |
0.0151 | 19.0 | 76 | 3.0277 |
0.0145 | 20.0 | 80 | 3.0303 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.13.1
- Tokenizers 0.14.1
Model tree for brettbbb/mc_cot_16
Base model
lmsys/vicuna-7b-v1.5