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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-finetuned-SQL-2 |
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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-finetuned-SQL-2 |
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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: 2.1014 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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: 0.1 |
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- training_steps: 20000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 2.2954 | 3.2 | 1000 | 1.8424 | |
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| 1.747 | 6.4 | 2000 | 1.7355 | |
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| 1.6037 | 9.6 | 3000 | 1.6513 | |
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| 1.4616 | 12.8 | 4000 | 1.6125 | |
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| 1.3183 | 16.0 | 5000 | 1.6114 | |
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| 1.1743 | 19.2 | 6000 | 1.6670 | |
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| 1.0421 | 22.4 | 7000 | 1.7143 | |
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| 0.9229 | 25.6 | 8000 | 1.7434 | |
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| 0.8166 | 28.8 | 9000 | 1.8055 | |
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| 0.7256 | 32.0 | 10000 | 1.8523 | |
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| 0.6435 | 35.2 | 11000 | 1.9160 | |
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| 0.5779 | 38.4 | 12000 | 1.9352 | |
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| 0.5209 | 41.6 | 13000 | 1.9740 | |
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| 0.4739 | 44.8 | 14000 | 2.0014 | |
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| 0.4353 | 48.0 | 15000 | 2.0192 | |
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| 0.4036 | 51.2 | 16000 | 2.0506 | |
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| 0.3814 | 54.4 | 17000 | 2.0678 | |
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| 0.3626 | 57.6 | 18000 | 2.0861 | |
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| 0.3504 | 60.8 | 19000 | 2.0940 | |
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| 0.3391 | 64.0 | 20000 | 2.1014 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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