phi-3-mini-LoRA
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: 0.5630
Model description
More information needed
Intended uses & limitations
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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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.7513 | 0.7233 | 100 | 0.5811 |
| 0.5704 | 1.4467 | 200 | 0.5683 |
| 0.5652 | 2.1700 | 300 | 0.5644 |
| 0.5637 | 2.8933 | 400 | 0.5630 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for Balab2021/phi-3-mini-LoRA
Base model
microsoft/Phi-3-mini-4k-instruct