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--- |
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license: mit |
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base_model: microsoft/deberta-v3-small |
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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-small-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-small-kaggle-mlm |
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This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6169 |
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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: 30 |
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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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| 3.0931 | 1.0 | 6848 | 2.8467 | |
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| 2.6186 | 2.0 | 13696 | 2.4089 | |
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| 2.3498 | 3.0 | 20544 | 2.2224 | |
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| 2.2399 | 4.0 | 27392 | 2.1105 | |
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| 2.1226 | 5.0 | 34240 | 2.0204 | |
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| 2.0768 | 6.0 | 41088 | 1.9402 | |
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| 2.0251 | 7.0 | 47936 | 1.8767 | |
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| 1.9587 | 8.0 | 54784 | 1.8527 | |
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| 1.9209 | 9.0 | 61632 | 1.8108 | |
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| 1.8829 | 10.0 | 68480 | 1.8113 | |
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| 1.8454 | 11.0 | 75328 | 1.7698 | |
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| 1.8077 | 12.0 | 82176 | 1.7504 | |
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| 1.7991 | 13.0 | 89024 | 1.7390 | |
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| 1.7896 | 14.0 | 95872 | 1.7138 | |
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| 1.7608 | 15.0 | 102720 | 1.6847 | |
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| 1.7636 | 16.0 | 109568 | 1.6863 | |
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| 1.7416 | 17.0 | 116416 | 1.6816 | |
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| 1.7363 | 18.0 | 123264 | 1.6651 | |
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| 1.7013 | 19.0 | 130112 | 1.6465 | |
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| 1.6828 | 20.0 | 136960 | 1.6528 | |
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| 1.6889 | 21.0 | 143808 | 1.6406 | |
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| 1.6882 | 22.0 | 150656 | 1.6358 | |
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| 1.6742 | 23.0 | 157504 | 1.6338 | |
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| 1.6657 | 24.0 | 164352 | 1.6062 | |
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| 1.6685 | 25.0 | 171200 | 1.6086 | |
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| 1.6701 | 26.0 | 178048 | 1.6256 | |
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| 1.6755 | 27.0 | 184896 | 1.6186 | |
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| 1.6505 | 28.0 | 191744 | 1.6013 | |
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| 1.6573 | 29.0 | 198592 | 1.6108 | |
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| 1.6497 | 30.0 | 205440 | 1.6009 | |
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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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