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--- |
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base_model: microsoft/Phi-3-mini-4k-instruct |
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library_name: peft |
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license: mit |
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tags: |
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- trl |
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- sft |
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- generated_from_trainer |
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model-index: |
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- name: phi-3-mini-QLoRA |
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results: [] |
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pipeline_tag: text-generation |
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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-mini-QLoRA |
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This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1546 |
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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: 0.0001 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 2.2359 | 0.1416 | 50 | 1.9291 | |
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| 1.5215 | 0.2833 | 100 | 1.2761 | |
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| 1.287 | 0.4249 | 150 | 1.2268 | |
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| 1.2613 | 0.5666 | 200 | 1.2073 | |
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| 1.2341 | 0.7082 | 250 | 1.1996 | |
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| 1.2037 | 0.8499 | 300 | 1.1953 | |
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| 1.2117 | 0.9915 | 350 | 1.1871 | |
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| 1.2023 | 1.1331 | 400 | 1.1813 | |
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| 1.1635 | 1.2748 | 450 | 1.1770 | |
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| 1.1689 | 1.4164 | 500 | 1.1732 | |
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| 1.2013 | 1.5581 | 550 | 1.1720 | |
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| 1.1853 | 1.6997 | 600 | 1.1675 | |
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| 1.1933 | 1.8414 | 650 | 1.1648 | |
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| 1.1774 | 1.9830 | 700 | 1.1619 | |
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| 1.1633 | 2.1246 | 750 | 1.1626 | |
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| 1.1756 | 2.2663 | 800 | 1.1593 | |
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| 1.1597 | 2.4079 | 850 | 1.1587 | |
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| 1.1599 | 2.5496 | 900 | 1.1562 | |
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| 1.1145 | 2.6912 | 950 | 1.1567 | |
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| 1.162 | 2.8329 | 1000 | 1.1553 | |
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| 1.1507 | 2.9745 | 1050 | 1.1546 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.43.3 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
