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README.md
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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-4-mini-instruct
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tags:
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- generated_from_trainer
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model-index:
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- name: phi4-lora-xaji0y6d-1742299723
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results: []
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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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# phi4-lora-xaji0y6d-1742299723
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This model is a fine-tuned version of [microsoft/Phi-4-mini-instruct](https://huggingface.co/microsoft/Phi-4-mini-instruct) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 25.3528
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- Perplexity: 102470071639.741
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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: 5e-05
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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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- gradient_accumulation_steps: 16
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- total_train_batch_size: 16
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- optimizer: Use adamw_hf with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.05
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Perplexity |
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|:-------------:|:------:|:----:|:---------------:|:----------------:|
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| 2.0923 | 1.3195 | 50 | 19.9230 | 449198544.2945 |
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| 0.0841 | 2.6389 | 100 | 24.5671 | 46702980507.7979 |
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| 0.0374 | 3.9584 | 150 | 25.3528 | 102470071639.741 |
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### Framework versions
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- PEFT 0.14.0
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- Transformers 4.48.2
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- Pytorch 2.5.1+cu121
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- Datasets 3.3.1
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- Tokenizers 0.21.0
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