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--- |
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license: mit |
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base_model: microsoft/deberta-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: deberta-finetuned |
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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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# deberta-finetuned |
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This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2464 |
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- Accuracy: 0.925 |
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- F1: 0.9496 |
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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: 5e-06 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| No log | 1.0 | 190 | 0.2784 | 0.9125 | 0.9412 | |
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| No log | 2.0 | 380 | 0.2370 | 0.9313 | 0.9536 | |
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| 0.3907 | 3.0 | 570 | 0.2328 | 0.925 | 0.9500 | |
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| 0.3907 | 4.0 | 760 | 0.2659 | 0.925 | 0.9504 | |
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| 0.3907 | 5.0 | 950 | 0.2464 | 0.925 | 0.9496 | |
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### Framework versions |
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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 |
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