phi2_fine_tune_istanbul_rugs
This model is a fine-tuned version of microsoft/phi-2 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 0.8105
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: 0.0008
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- training_steps: 300
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.6408 | 0.72 | 10 | 0.5720 |
0.4116 | 1.45 | 20 | 0.5234 |
0.3467 | 2.17 | 30 | 0.5068 |
0.328 | 2.9 | 40 | 0.4990 |
0.3013 | 3.62 | 50 | 0.5022 |
0.267 | 4.34 | 60 | 0.5051 |
0.2407 | 5.07 | 70 | 0.5151 |
0.2084 | 5.79 | 80 | 0.5329 |
0.1821 | 6.52 | 90 | 0.5566 |
0.1635 | 7.24 | 100 | 0.5996 |
0.1431 | 7.96 | 110 | 0.6137 |
0.1164 | 8.69 | 120 | 0.6461 |
0.1045 | 9.41 | 130 | 0.6714 |
0.0903 | 10.14 | 140 | 0.6719 |
0.0773 | 10.86 | 150 | 0.6802 |
0.0653 | 11.58 | 160 | 0.7234 |
0.0595 | 12.31 | 170 | 0.7497 |
0.0523 | 13.03 | 180 | 0.7281 |
0.0453 | 13.76 | 190 | 0.7439 |
0.0405 | 14.48 | 200 | 0.7655 |
0.0363 | 15.2 | 210 | 0.7674 |
0.0323 | 15.93 | 220 | 0.7835 |
0.0293 | 16.65 | 230 | 0.7924 |
0.0276 | 17.38 | 240 | 0.7981 |
0.0257 | 18.1 | 250 | 0.8023 |
0.0252 | 18.82 | 260 | 0.8019 |
0.0236 | 19.55 | 270 | 0.8040 |
0.023 | 20.27 | 280 | 0.8089 |
0.0232 | 21.0 | 290 | 0.8104 |
0.0231 | 21.72 | 300 | 0.8105 |
Framework versions
- PEFT 0.9.0
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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Model tree for aguglaniAI/phi2_fine_tune_istanbul_rugs
Base model
microsoft/phi-2
Adapter
this model