PHI30512HMAB6H
This model is a fine-tuned version of microsoft/Phi-3-mini-4k-instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0698
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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 80
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
4.4764 | 0.09 | 10 | 1.7039 |
0.6874 | 0.18 | 20 | 0.4076 |
0.3403 | 0.27 | 30 | 0.2637 |
0.2668 | 0.36 | 40 | 0.2667 |
0.8232 | 0.45 | 50 | 3.1025 |
0.8435 | 0.54 | 60 | 0.2217 |
0.2786 | 0.63 | 70 | 0.2215 |
0.2253 | 0.73 | 80 | 0.2019 |
0.1871 | 0.82 | 90 | 0.1830 |
0.1871 | 0.91 | 100 | 0.1695 |
0.2185 | 1.0 | 110 | 0.2040 |
0.1712 | 1.09 | 120 | 0.1659 |
0.4398 | 1.18 | 130 | 0.2223 |
1.8534 | 1.27 | 140 | 2.5467 |
1.547 | 1.36 | 150 | 0.7915 |
0.6568 | 1.45 | 160 | 0.4273 |
0.3954 | 1.54 | 170 | 0.4106 |
0.3571 | 1.63 | 180 | 0.3610 |
0.2652 | 1.72 | 190 | 0.1875 |
0.207 | 1.81 | 200 | 0.1718 |
0.1613 | 1.9 | 210 | 0.1431 |
0.1411 | 1.99 | 220 | 0.1365 |
0.1256 | 2.08 | 230 | 0.1349 |
0.1252 | 2.18 | 240 | 0.1040 |
0.1131 | 2.27 | 250 | 0.0991 |
0.1023 | 2.36 | 260 | 0.0855 |
0.0836 | 2.45 | 270 | 0.0725 |
0.082 | 2.54 | 280 | 0.0696 |
0.0906 | 2.63 | 290 | 0.0696 |
0.075 | 2.72 | 300 | 0.0694 |
0.0766 | 2.81 | 310 | 0.0683 |
0.0741 | 2.9 | 320 | 0.0700 |
0.0664 | 2.99 | 330 | 0.0698 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
Model tree for Litzy619/PHI30512HMAB6H
Base model
microsoft/Phi-3-mini-4k-instruct