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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: Phi-3.5-MultiCap-tool-lora |
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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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# Phi-3.5-MultiCap-tool-lora |
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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: 0.4902 |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 128 |
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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: 0.03 |
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- num_epochs: 6 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.7255 | 0.2256 | 50 | 0.7138 | |
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| 0.4783 | 0.4512 | 100 | 0.4788 | |
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| 0.4616 | 0.6768 | 150 | 0.4543 | |
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| 0.4794 | 0.9024 | 200 | 0.4437 | |
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| 0.4174 | 1.1280 | 250 | 0.4357 | |
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| 0.4097 | 1.3536 | 300 | 0.4310 | |
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| 0.3829 | 1.5792 | 350 | 0.4280 | |
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| 0.4358 | 1.8049 | 400 | 0.4264 | |
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| 0.4013 | 2.0305 | 450 | 0.4261 | |
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| 0.3685 | 2.2561 | 500 | 0.4268 | |
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| 0.3823 | 2.4817 | 550 | 0.4276 | |
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| 0.401 | 2.7073 | 600 | 0.4294 | |
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| 0.3975 | 2.9329 | 650 | 0.4310 | |
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| 0.4012 | 3.1585 | 700 | 0.4373 | |
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| 0.3497 | 3.3841 | 750 | 0.4401 | |
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| 0.3613 | 3.6097 | 800 | 0.4456 | |
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| 0.3649 | 3.8353 | 850 | 0.4522 | |
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| 0.3384 | 4.0609 | 900 | 0.4575 | |
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| 0.3241 | 4.2865 | 950 | 0.4628 | |
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| 0.322 | 4.5121 | 1000 | 0.4662 | |
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| 0.3397 | 4.7377 | 1050 | 0.4720 | |
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| 0.3228 | 4.9633 | 1100 | 0.4788 | |
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| 0.3391 | 5.1889 | 1150 | 0.4820 | |
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| 0.3369 | 5.4146 | 1200 | 0.4861 | |
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| 0.3424 | 5.6402 | 1250 | 0.4873 | |
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| 0.3302 | 5.8658 | 1300 | 0.4902 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu124 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
