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--- |
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license: mit |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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datasets: |
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- scitldr |
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base_model: microsoft/phi-1_5 |
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model-index: |
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- name: Phi-1.5-Summarization-QLoRA |
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results: [] |
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pipeline_tag: summarization |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Phi-1.5 Summarization (QLoRA) |
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This model is a fine-tuned version of [microsoft/phi-1_5](https://huggingface.co/microsoft/phi-1_5) on the scitldr dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.5866 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 2 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 2.5683 | 0.25 | 500 | 2.6196 | |
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| 2.5308 | 0.5 | 1000 | 2.5992 | |
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| 2.558 | 0.75 | 1500 | 2.5886 | |
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| 2.4925 | 1.0 | 2000 | 2.5827 | |
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| 2.3252 | 1.26 | 2500 | 2.5948 | |
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| 2.3128 | 1.51 | 3000 | 2.5879 | |
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| 2.4622 | 1.76 | 3500 | 2.5866 | |
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### Framework versions |
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- PEFT 0.9.0 |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
