Summarization-Phi-3
This model is a fine-tuned version of microsoft/Phi-3-mini-128k-instruct on the scitldr dataset. It achieves the following results on the evaluation set:
- Loss: 2.1554
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: 0.0002
- 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.0689 | 0.2510 | 500 | 2.1439 |
| 2.0455 | 0.5020 | 1000 | 2.1388 |
| 2.0665 | 0.7530 | 1500 | 2.1349 |
| 2.0481 | 1.0040 | 2000 | 2.1308 |
| 1.9051 | 1.2550 | 2500 | 2.1573 |
| 1.8524 | 1.5060 | 3000 | 2.1588 |
| 1.8247 | 1.7570 | 3500 | 2.1554 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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Model tree for pkbiswas/Phi-3-Summarization-QLoRa
Base model
microsoft/Phi-3-mini-128k-instruct