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--- |
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base_model: microsoft/phi-2 |
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library_name: peft |
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license: mit |
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metrics: |
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- accuracy |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: microsoft_ph2_isco_classification |
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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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# microsoft_ph2_isco_classification |
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This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6020 |
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- Balanced Accuracy: 0.6060 |
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- Accuracy: 0.6301 |
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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: 0.0001 |
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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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Balanced Accuracy | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------:| |
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| 0.3013 | 1.0 | 2641 | 1.6020 | 0.6060 | 0.6301 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
