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--- |
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license: mit |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: microsoft/phi-2 |
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model-index: |
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- name: fine-tuning-Phi2-with-webglm-qa-with-lora_8 |
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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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# fine-tuning-Phi2-with-webglm-qa-with-lora_8 |
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This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0935 |
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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: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 5 |
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- total_train_batch_size: 10 |
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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_steps: 60 |
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- training_steps: 1000 |
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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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| 7.1823 | 0.31 | 20 | 6.1082 | |
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| 4.0 | 0.63 | 40 | 0.9863 | |
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| 0.7159 | 0.94 | 60 | 0.6293 | |
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| 0.4994 | 1.26 | 80 | 0.4239 | |
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| 0.3187 | 1.57 | 100 | 0.3044 | |
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| 0.251 | 1.89 | 120 | 0.2567 | |
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| 0.2189 | 2.2 | 140 | 0.2206 | |
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| 0.1869 | 2.52 | 160 | 0.2000 | |
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| 0.1741 | 2.83 | 180 | 0.1781 | |
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| 0.1439 | 3.14 | 200 | 0.1638 | |
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| 0.1543 | 3.46 | 220 | 0.1550 | |
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| 0.1428 | 3.77 | 240 | 0.1455 | |
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| 0.127 | 4.09 | 260 | 0.1394 | |
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| 0.1206 | 4.4 | 280 | 0.1314 | |
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| 0.1206 | 4.72 | 300 | 0.1298 | |
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| 0.1162 | 5.03 | 320 | 0.1246 | |
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| 0.109 | 5.35 | 340 | 0.1235 | |
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| 0.1088 | 5.66 | 360 | 0.1190 | |
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| 0.1062 | 5.97 | 380 | 0.1157 | |
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| 0.0938 | 6.29 | 400 | 0.1146 | |
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| 0.0945 | 6.6 | 420 | 0.1133 | |
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| 0.1012 | 6.92 | 440 | 0.1105 | |
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| 0.0881 | 7.23 | 460 | 0.1109 | |
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| 0.0897 | 7.55 | 480 | 0.1091 | |
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| 0.0837 | 7.86 | 500 | 0.1060 | |
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| 0.0899 | 8.18 | 520 | 0.1051 | |
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| 0.0803 | 8.49 | 540 | 0.1041 | |
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| 0.0792 | 8.81 | 560 | 0.1021 | |
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| 0.0885 | 9.12 | 580 | 0.1000 | |
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| 0.0844 | 9.43 | 600 | 0.1004 | |
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| 0.0704 | 9.75 | 620 | 0.0992 | |
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| 0.0681 | 10.06 | 640 | 0.0994 | |
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| 0.0727 | 10.38 | 660 | 0.0977 | |
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| 0.0712 | 10.69 | 680 | 0.0970 | |
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| 0.073 | 11.01 | 700 | 0.0971 | |
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| 0.0683 | 11.32 | 720 | 0.0974 | |
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| 0.0682 | 11.64 | 740 | 0.0964 | |
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| 0.0716 | 11.95 | 760 | 0.0962 | |
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| 0.0645 | 12.26 | 780 | 0.0948 | |
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| 0.0662 | 12.58 | 800 | 0.0947 | |
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| 0.0677 | 12.89 | 820 | 0.0947 | |
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| 0.0626 | 13.21 | 840 | 0.0953 | |
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| 0.0628 | 13.52 | 860 | 0.0946 | |
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| 0.0642 | 13.84 | 880 | 0.0937 | |
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| 0.0641 | 14.15 | 900 | 0.0939 | |
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| 0.0587 | 14.47 | 920 | 0.0939 | |
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| 0.0664 | 14.78 | 940 | 0.0933 | |
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| 0.061 | 15.09 | 960 | 0.0931 | |
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| 0.0596 | 15.41 | 980 | 0.0934 | |
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| 0.0646 | 15.72 | 1000 | 0.0935 | |
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### Framework versions |
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- PEFT 0.7.1 |
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- Transformers 4.36.2 |
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- Pytorch 2.0.0 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
