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--- |
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license: other |
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base_model: microsoft/phi-1_5 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: phi-1_5-psychology |
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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-1_5-psychology |
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This model is a fine-tuned version of [microsoft/phi-1_5](https://huggingface.co/microsoft/phi-1_5) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7574 |
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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: 0.0002 |
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- train_batch_size: 4 |
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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: cosine |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.8667 | 0.04 | 100 | 0.8554 | |
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| 0.8401 | 0.09 | 200 | 0.8524 | |
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| 0.8492 | 0.13 | 300 | 0.8437 | |
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| 0.8563 | 0.18 | 400 | 0.8393 | |
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| 0.8353 | 0.22 | 500 | 0.8367 | |
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| 0.8232 | 0.26 | 600 | 0.8305 | |
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| 0.8299 | 0.31 | 700 | 0.8226 | |
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| 0.8307 | 0.35 | 800 | 0.8233 | |
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| 0.8087 | 0.39 | 900 | 0.8170 | |
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| 0.8124 | 0.44 | 1000 | 0.8160 | |
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| 0.7943 | 0.48 | 1100 | 0.8103 | |
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| 0.7924 | 0.53 | 1200 | 0.8076 | |
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| 0.7918 | 0.57 | 1300 | 0.8026 | |
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| 0.807 | 0.61 | 1400 | 0.8012 | |
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| 0.788 | 0.66 | 1500 | 0.8034 | |
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| 0.7946 | 0.7 | 1600 | 0.7946 | |
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| 0.7959 | 0.75 | 1700 | 0.7926 | |
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| 0.7878 | 0.79 | 1800 | 0.7921 | |
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| 0.754 | 0.83 | 1900 | 0.7890 | |
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| 0.7762 | 0.88 | 2000 | 0.7850 | |
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| 0.7651 | 0.92 | 2100 | 0.7849 | |
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| 0.7868 | 0.97 | 2200 | 0.7855 | |
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| 0.7651 | 1.01 | 2300 | 0.7820 | |
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| 0.7323 | 1.05 | 2400 | 0.7818 | |
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| 0.7316 | 1.1 | 2500 | 0.7804 | |
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| 0.7311 | 1.14 | 2600 | 0.7808 | |
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| 0.7221 | 1.18 | 2700 | 0.7782 | |
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| 0.722 | 1.23 | 2800 | 0.7736 | |
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| 0.7217 | 1.27 | 2900 | 0.7780 | |
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| 0.7226 | 1.32 | 3000 | 0.7730 | |
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| 0.7305 | 1.36 | 3100 | 0.7731 | |
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| 0.7237 | 1.4 | 3200 | 0.7712 | |
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| 0.7127 | 1.45 | 3300 | 0.7710 | |
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| 0.7252 | 1.49 | 3400 | 0.7699 | |
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| 0.7076 | 1.54 | 3500 | 0.7687 | |
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| 0.7185 | 1.58 | 3600 | 0.7672 | |
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| 0.6921 | 1.62 | 3700 | 0.7639 | |
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| 0.6882 | 1.67 | 3800 | 0.7642 | |
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| 0.7184 | 1.71 | 3900 | 0.7633 | |
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| 0.7048 | 1.76 | 4000 | 0.7601 | |
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| 0.7136 | 1.8 | 4100 | 0.7598 | |
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| 0.7063 | 1.84 | 4200 | 0.7591 | |
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| 0.7054 | 1.89 | 4300 | 0.7589 | |
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| 0.6945 | 1.93 | 4400 | 0.7564 | |
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| 0.6955 | 1.97 | 4500 | 0.7544 | |
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| 0.6869 | 2.02 | 4600 | 0.7536 | |
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| 0.6477 | 2.06 | 4700 | 0.7566 | |
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| 0.6593 | 2.11 | 4800 | 0.7568 | |
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| 0.6441 | 2.15 | 4900 | 0.7562 | |
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| 0.6527 | 2.19 | 5000 | 0.7574 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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