phi-2-sft-openhermes-128k-v2
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: 1.0663
- Model Preparation Time: 0.0259
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: 1.5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
Training Loss |
Epoch |
Step |
Validation Loss |
Model Preparation Time |
1.0842 |
0.0809 |
200 |
1.0744 |
0.0259 |
1.0767 |
0.1617 |
400 |
1.0724 |
0.0259 |
1.0997 |
0.2426 |
600 |
1.0716 |
0.0259 |
1.0758 |
0.3234 |
800 |
1.0707 |
0.0259 |
1.0949 |
0.4043 |
1000 |
1.0697 |
0.0259 |
1.0892 |
0.4851 |
1200 |
1.0687 |
0.0259 |
1.0876 |
0.5660 |
1400 |
1.0682 |
0.0259 |
1.0873 |
0.6469 |
1600 |
1.0676 |
0.0259 |
1.0679 |
0.7277 |
1800 |
1.0671 |
0.0259 |
1.0802 |
0.8086 |
2000 |
1.0669 |
0.0259 |
1.0823 |
0.8894 |
2200 |
1.0667 |
0.0259 |
1.0812 |
0.9703 |
2400 |
1.0663 |
0.0259 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1