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--- |
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library_name: transformers |
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license: mit |
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base_model: sercetexam9/deberta-v3-large-finetuned-augmentation-LUNAR-TAPT-DAIR |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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- accuracy |
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model-index: |
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- name: deberta-v3-large-finetuned-augmentation-LUNAR-TAPT-DAIR-finetuned-augmentation-LUNAR-TAPT-macro |
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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-v3-large-finetuned-augmentation-LUNAR-TAPT-DAIR-finetuned-augmentation-LUNAR-TAPT-macro |
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This model is a fine-tuned version of [sercetexam9/deberta-v3-large-finetuned-augmentation-LUNAR-TAPT-DAIR](https://huggingface.co/sercetexam9/deberta-v3-large-finetuned-augmentation-LUNAR-TAPT-DAIR) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1447 |
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- F1: 0.9370 |
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- Roc Auc: 0.9481 |
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- Accuracy: 0.8545 |
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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_steps: 100 |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| |
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| 0.1249 | 1.0 | 421 | 0.1447 | 0.9370 | 0.9481 | 0.8545 | |
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| 0.1132 | 2.0 | 842 | 0.1485 | 0.9344 | 0.9512 | 0.8634 | |
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| 0.0924 | 3.0 | 1263 | 0.1491 | 0.9324 | 0.9528 | 0.8581 | |
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| 0.0679 | 4.0 | 1684 | 0.1779 | 0.9302 | 0.9433 | 0.8515 | |
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| 0.0844 | 5.0 | 2105 | 0.1748 | 0.9264 | 0.9429 | 0.8539 | |
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### Framework versions |
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- Transformers 4.45.1 |
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- Pytorch 2.4.0 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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