sft-microsoft-phi2-on-memory_dialoges
This model is a fine-tuned version of microsoft/phi-2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6715
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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 5
- total_train_batch_size: 10
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.0517 | 0.2 | 20 | 1.9505 |
1.7337 | 0.4 | 40 | 1.2702 |
0.9881 | 0.6 | 60 | 0.8091 |
0.7869 | 0.8 | 80 | 0.7450 |
0.7454 | 0.99 | 100 | 0.7252 |
0.7128 | 1.19 | 120 | 0.7143 |
0.7142 | 1.39 | 140 | 0.7064 |
0.6921 | 1.59 | 160 | 0.7011 |
0.688 | 1.79 | 180 | 0.6962 |
0.7061 | 1.99 | 200 | 0.6918 |
0.6744 | 2.19 | 220 | 0.6898 |
0.6771 | 2.39 | 240 | 0.6854 |
0.6795 | 2.58 | 260 | 0.6833 |
0.661 | 2.78 | 280 | 0.6802 |
0.6596 | 2.98 | 300 | 0.6793 |
0.6431 | 3.18 | 320 | 0.6780 |
0.6604 | 3.38 | 340 | 0.6766 |
0.6404 | 3.58 | 360 | 0.6757 |
0.6571 | 3.78 | 380 | 0.6740 |
0.6611 | 3.98 | 400 | 0.6733 |
0.6381 | 4.17 | 420 | 0.6732 |
0.6372 | 4.37 | 440 | 0.6721 |
0.639 | 4.57 | 460 | 0.6718 |
0.6506 | 4.77 | 480 | 0.6717 |
0.6226 | 4.97 | 500 | 0.6715 |
Framework versions
- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.15.0
- Tokenizers 0.15.1
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