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--- |
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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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model-index: |
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- name: deberta-v3-large-kaggle-mlm |
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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-kaggle-mlm |
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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: 1.3182 |
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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: 25 |
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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 | |
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|:-------------:|:-----:|:------:|:---------------:| |
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| 3.1114 | 1.0 | 6848 | 2.6616 | |
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| 2.2122 | 2.0 | 13696 | 1.9734 | |
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| 2.0848 | 3.0 | 20544 | 1.9930 | |
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| 1.8056 | 4.0 | 27392 | 1.7167 | |
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| 1.7003 | 5.0 | 34240 | 1.8419 | |
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| 1.6414 | 6.0 | 41088 | 1.5828 | |
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| 1.583 | 7.0 | 47936 | 1.5298 | |
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| 1.5245 | 8.0 | 54784 | 1.4964 | |
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| 1.491 | 9.0 | 61632 | 1.4671 | |
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| 1.4662 | 10.0 | 68480 | 1.4805 | |
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| 1.426 | 11.0 | 75328 | 1.4506 | |
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| 1.3924 | 12.0 | 82176 | 1.4272 | |
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| 1.3797 | 13.0 | 89024 | 1.4092 | |
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| 1.3713 | 14.0 | 95872 | 1.3947 | |
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| 1.3444 | 15.0 | 102720 | 1.3765 | |
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| 1.3414 | 16.0 | 109568 | 1.3636 | |
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| 1.3256 | 17.0 | 116416 | 1.3700 | |
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| 1.3084 | 18.0 | 123264 | 1.3607 | |
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| 1.2925 | 19.0 | 130112 | 1.3428 | |
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| 1.2615 | 20.0 | 136960 | 1.3483 | |
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| 1.2733 | 21.0 | 143808 | 1.3440 | |
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| 1.2809 | 22.0 | 150656 | 1.3314 | |
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| 1.2576 | 23.0 | 157504 | 1.3388 | |
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| 1.2606 | 24.0 | 164352 | 1.3126 | |
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| 1.2608 | 25.0 | 171200 | 1.3211 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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