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--- |
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library_name: transformers |
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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_textclassification |
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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_textclassification |
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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: 0.2786 |
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- Accuracy: 0.9467 |
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- F1: 0.9622 |
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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: 1e-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: 3 |
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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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| 0.2349 | 1.0 | 1520 | 0.2316 | 0.9388 | 0.9565 | |
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| 0.1801 | 2.0 | 3040 | 0.2382 | 0.9467 | 0.9621 | |
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| 0.0914 | 3.0 | 4560 | 0.2786 | 0.9467 | 0.9622 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 2.4.0 |
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- Tokenizers 0.19.1 |
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