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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: group3_non_all_zero |
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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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# group3_non_all_zero |
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This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0497 |
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- Precision: 0.0638 |
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- Recall: 0.2421 |
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- F1: 0.1009 |
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- Accuracy: 0.9339 |
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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: 3e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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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: 15 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 55 | 1.1877 | 0.0140 | 0.25 | 0.0265 | 0.7339 | |
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| No log | 2.0 | 110 | 0.9789 | 0.0219 | 0.2041 | 0.0395 | 0.8081 | |
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| No log | 3.0 | 165 | 1.0274 | 0.0385 | 0.2437 | 0.0665 | 0.8703 | |
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| No log | 4.0 | 220 | 1.1138 | 0.0225 | 0.1820 | 0.0401 | 0.8343 | |
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| No log | 5.0 | 275 | 1.1690 | 0.0335 | 0.2184 | 0.0581 | 0.8702 | |
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| No log | 6.0 | 330 | 1.3425 | 0.0421 | 0.2310 | 0.0712 | 0.8972 | |
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| No log | 7.0 | 385 | 1.5089 | 0.0445 | 0.2342 | 0.0748 | 0.9079 | |
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| No log | 8.0 | 440 | 1.5614 | 0.0466 | 0.2453 | 0.0783 | 0.9119 | |
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| No log | 9.0 | 495 | 1.7200 | 0.0534 | 0.2453 | 0.0876 | 0.9220 | |
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| 0.5787 | 10.0 | 550 | 1.7086 | 0.0447 | 0.2453 | 0.0756 | 0.9098 | |
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| 0.5787 | 11.0 | 605 | 1.8784 | 0.0553 | 0.2342 | 0.0895 | 0.9263 | |
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| 0.5787 | 12.0 | 660 | 1.9659 | 0.0589 | 0.2421 | 0.0947 | 0.9299 | |
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| 0.5787 | 13.0 | 715 | 1.9472 | 0.0600 | 0.2437 | 0.0963 | 0.9297 | |
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| 0.5787 | 14.0 | 770 | 2.0058 | 0.0605 | 0.2373 | 0.0964 | 0.9310 | |
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| 0.5787 | 15.0 | 825 | 2.0497 | 0.0638 | 0.2421 | 0.1009 | 0.9339 | |
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### Framework versions |
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- Transformers 4.30.0 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.13.3 |
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