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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-v3-large |
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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: cs221-deberta-v3-large-eng-pt |
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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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# cs221-deberta-v3-large-eng-pt |
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This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3691 |
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- F1: 0.7676 |
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- Roc Auc: 0.8216 |
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- Accuracy: 0.6034 |
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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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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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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| 0.4687 | 1.0 | 173 | 0.4601 | 0.4113 | 0.6309 | 0.3103 | |
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| 0.3504 | 2.0 | 346 | 0.3652 | 0.6879 | 0.7645 | 0.4397 | |
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| 0.2659 | 3.0 | 519 | 0.3636 | 0.7057 | 0.7616 | 0.4397 | |
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| 0.1696 | 4.0 | 692 | 0.3691 | 0.7676 | 0.8216 | 0.6034 | |
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| 0.1001 | 5.0 | 865 | 0.4142 | 0.7647 | 0.8246 | 0.5172 | |
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| 0.0699 | 6.0 | 1038 | 0.4698 | 0.7530 | 0.8034 | 0.4828 | |
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| 0.049 | 7.0 | 1211 | 0.5140 | 0.7219 | 0.7911 | 0.5 | |
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| 0.0253 | 8.0 | 1384 | 0.5917 | 0.7603 | 0.8191 | 0.5345 | |
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### Framework versions |
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- Transformers 4.47.0 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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