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license: mit |
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tags: |
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- generated_from_trainer |
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datasets: SetFit/subj |
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metrics: |
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- accuracy |
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model-index: |
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- name: microsoft-deberta-v3-large_cls_subj |
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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-deberta-v3-large_cls_subj |
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This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co./microsoft/deberta-v3-large) on [subj](https://huggingface.co./datasets/SetFit/subj) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1525 |
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- Accuracy: 0.976 |
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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: 2e-05 |
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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: cosine |
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- lr_scheduler_warmup_ratio: 0.2 |
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- num_epochs: 5 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.2629 | 1.0 | 500 | 0.1519 | 0.955 | |
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| 0.1232 | 2.0 | 1000 | 0.1121 | 0.974 | |
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| 0.0535 | 3.0 | 1500 | 0.1341 | 0.974 | |
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| 0.0152 | 4.0 | 2000 | 0.1794 | 0.969 | |
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| 0.0043 | 5.0 | 2500 | 0.1525 | 0.976 | |
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### Framework versions |
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- Transformers 4.25.1 |
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- Pytorch 1.13.0+cu116 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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