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--- |
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library_name: peft |
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license: other |
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base_model: microsoft/Phi-3-mini-4k-instruct |
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tags: |
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- llama-factory |
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- lora |
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- generated_from_trainer |
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model-index: |
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- name: 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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# lora |
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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 flock_task4_tranning dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1499 |
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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: 2 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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- total_eval_batch_size: 2 |
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- optimizer: Use adamw_torch 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: 0.1 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.0681 | 0.0501 | 50 | 1.2795 | |
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| 1.0394 | 0.1002 | 100 | 1.2304 | |
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| 0.9251 | 0.1502 | 150 | 1.2384 | |
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| 1.0063 | 0.2003 | 200 | 1.2121 | |
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| 0.9905 | 0.2504 | 250 | 1.2024 | |
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| 0.9761 | 0.3005 | 300 | 1.1887 | |
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| 0.8606 | 0.3505 | 350 | 1.1863 | |
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| 0.9137 | 0.4006 | 400 | 1.1841 | |
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| 0.9647 | 0.4507 | 450 | 1.1794 | |
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| 0.9091 | 0.5008 | 500 | 1.1720 | |
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| 0.8968 | 0.5508 | 550 | 1.1639 | |
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| 0.9193 | 0.6009 | 600 | 1.1597 | |
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| 0.8827 | 0.6510 | 650 | 1.1622 | |
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| 0.895 | 0.7011 | 700 | 1.1525 | |
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| 0.9329 | 0.7511 | 750 | 1.1563 | |
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| 0.8991 | 0.8012 | 800 | 1.1525 | |
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| 0.8639 | 0.8513 | 850 | 1.1508 | |
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| 0.8723 | 0.9014 | 900 | 1.1498 | |
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| 0.9658 | 0.9514 | 950 | 1.1497 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.48.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
