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--- |
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library_name: peft |
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license: mit |
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base_model: microsoft/Phi-3.5-mini-instruct |
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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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model-index: |
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- name: Phi-3.5-Mini-Instruct-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-3.5-Mini-Instruct-Summarization-QLoRa |
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This model is a fine-tuned version of [microsoft/Phi-3.5-mini-instruct](https://huggingface.co/microsoft/Phi-3.5-mini-instruct) on the scitldr dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.1376 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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Summarization |
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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: Use paged_adamw_32bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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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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| 2.0519 | 0.2510 | 500 | 2.1280 | |
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| 2.0279 | 0.5020 | 1000 | 2.1223 | |
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| 2.0514 | 0.7530 | 1500 | 2.1131 | |
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| 2.0313 | 1.0040 | 2000 | 2.1142 | |
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| 1.8923 | 1.2550 | 2500 | 2.1390 | |
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| 1.8487 | 1.5060 | 3000 | 2.1375 | |
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| 1.819 | 1.7570 | 3500 | 2.1376 | |
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### Framework versions |
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- PEFT 0.14.0 |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
