Phi-1.5 Summarization (LoRA)
This model is a fine-tuned version of microsoft/phi-1_5 on the scitldr dataset. It achieves the following results on the evaluation set:
- Loss: 2.6242
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: 0.001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.6014 | 0.25 | 500 | 2.6496 |
| 2.5756 | 0.5 | 1000 | 2.6445 |
| 2.5945 | 0.75 | 1500 | 2.6291 |
| 2.5251 | 1.0 | 2000 | 2.6133 |
| 2.3196 | 1.26 | 2500 | 2.6370 |
| 2.2953 | 1.51 | 3000 | 2.6325 |
| 2.452 | 1.76 | 3500 | 2.6242 |
Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Downloads last month
- 6
Inference API (serverless) does not yet support peft models for this pipeline type.
Model tree for pkbiswas/Phi-1_5-Summarization-LoRa
Base model
microsoft/phi-1_5