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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: group2_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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# group2_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: 0.3907 |
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- Precision: 0.0415 |
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- Recall: 0.086 |
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- F1: 0.0560 |
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- Accuracy: 0.9044 |
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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: 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: 6 |
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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 | 172 | 0.2512 | 0.0608 | 0.044 | 0.0510 | 0.9439 | |
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| No log | 2.0 | 344 | 0.2667 | 0.0355 | 0.048 | 0.0408 | 0.9194 | |
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| 0.4561 | 3.0 | 516 | 0.2883 | 0.0445 | 0.078 | 0.0566 | 0.9198 | |
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| 0.4561 | 4.0 | 688 | 0.3610 | 0.0379 | 0.092 | 0.0537 | 0.8968 | |
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| 0.4561 | 5.0 | 860 | 0.3840 | 0.0528 | 0.094 | 0.0676 | 0.9095 | |
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| 0.1508 | 6.0 | 1032 | 0.3907 | 0.0415 | 0.086 | 0.0560 | 0.9044 | |
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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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