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--- |
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base_model: microsoft/Phi-3.5-mini-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: question-generator-v2 |
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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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# question-generator-v2 |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7497 |
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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: 0.0005 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 3 |
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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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| 1.0483 | 0.0967 | 50 | 0.9260 | |
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| 0.8577 | 0.1934 | 100 | 0.8202 | |
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| 0.7996 | 0.2901 | 150 | 0.7895 | |
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| 0.7802 | 0.3868 | 200 | 0.7784 | |
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| 0.7671 | 0.4836 | 250 | 0.7721 | |
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| 0.761 | 0.5803 | 300 | 0.7688 | |
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| 0.7587 | 0.6770 | 350 | 0.7663 | |
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| 0.7529 | 0.7737 | 400 | 0.7637 | |
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| 0.7562 | 0.8704 | 450 | 0.7616 | |
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| 0.7507 | 0.9671 | 500 | 0.7602 | |
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| 0.7274 | 1.0638 | 550 | 0.7589 | |
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| 0.7422 | 1.1605 | 600 | 0.7574 | |
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| 0.735 | 1.2573 | 650 | 0.7571 | |
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| 0.7367 | 1.3540 | 700 | 0.7555 | |
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| 0.7471 | 1.4507 | 750 | 0.7549 | |
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| 0.7404 | 1.5474 | 800 | 0.7541 | |
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| 0.742 | 1.6441 | 850 | 0.7533 | |
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| 0.7385 | 1.7408 | 900 | 0.7530 | |
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| 0.7352 | 1.8375 | 950 | 0.7525 | |
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| 0.7323 | 1.9342 | 1000 | 0.7516 | |
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| 0.7328 | 2.0309 | 1050 | 0.7515 | |
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| 0.7264 | 2.1277 | 1100 | 0.7510 | |
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| 0.704 | 2.2244 | 1150 | 0.7505 | |
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| 0.7242 | 2.3211 | 1200 | 0.7510 | |
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| 0.7203 | 2.4178 | 1250 | 0.7502 | |
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| 0.7285 | 2.5145 | 1300 | 0.7499 | |
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| 0.7192 | 2.6112 | 1350 | 0.7502 | |
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| 0.7204 | 2.7079 | 1400 | 0.7497 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.42.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
