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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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- generated_from_trainer |
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model-index: |
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- name: phi3.5-mini-adapter_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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# phi3.5-mini-adapter_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: 0.1344 |
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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: 1e-05 |
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- train_batch_size: 24 |
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- eval_batch_size: 24 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 48 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.05 |
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- num_epochs: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 17.6422 | 0.4545 | 10 | 17.2166 | |
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| 13.0308 | 0.9091 | 20 | 12.5267 | |
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| 8.4662 | 1.3636 | 30 | 7.9483 | |
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| 2.4521 | 1.8182 | 40 | 1.3982 | |
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| 0.3917 | 2.2727 | 50 | 0.3427 | |
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| 0.3042 | 2.7273 | 60 | 0.3092 | |
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| 0.2051 | 3.1818 | 70 | 0.2451 | |
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| 0.2043 | 3.6364 | 80 | 0.2022 | |
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| 0.1599 | 4.0909 | 90 | 0.1907 | |
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| 0.1658 | 4.5455 | 100 | 0.1727 | |
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| 0.1527 | 5.0 | 110 | 0.1595 | |
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| 0.1281 | 5.4545 | 120 | 0.1501 | |
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| 0.1079 | 5.9091 | 130 | 0.1435 | |
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| 0.0896 | 6.3636 | 140 | 0.1369 | |
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| 0.097 | 6.8182 | 150 | 0.1340 | |
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| 0.0841 | 7.2727 | 160 | 0.1449 | |
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| 0.0771 | 7.7273 | 170 | 0.1344 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.43.1 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
