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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: deberta-v3-large__sst2__train-8-2 |
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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__sst2__train-8-2 |
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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: 0.6794 |
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- Accuracy: 0.6063 |
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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: 4 |
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- eval_batch_size: 4 |
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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: 50 |
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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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| 0.6942 | 1.0 | 3 | 0.7940 | 0.25 | |
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| 0.6068 | 2.0 | 6 | 0.9326 | 0.25 | |
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| 0.6553 | 3.0 | 9 | 0.7979 | 0.25 | |
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| 0.475 | 4.0 | 12 | 0.7775 | 0.25 | |
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| 0.377 | 5.0 | 15 | 0.7477 | 0.25 | |
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| 0.3176 | 6.0 | 18 | 0.6856 | 0.75 | |
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| 0.2708 | 7.0 | 21 | 0.6554 | 0.75 | |
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| 0.2855 | 8.0 | 24 | 0.8129 | 0.5 | |
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| 0.148 | 9.0 | 27 | 0.7074 | 0.75 | |
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| 0.0947 | 10.0 | 30 | 0.7090 | 0.75 | |
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| 0.049 | 11.0 | 33 | 0.7885 | 0.75 | |
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| 0.0252 | 12.0 | 36 | 0.9203 | 0.75 | |
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| 0.0165 | 13.0 | 39 | 1.0937 | 0.75 | |
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| 0.0084 | 14.0 | 42 | 1.2502 | 0.75 | |
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| 0.0059 | 15.0 | 45 | 1.3726 | 0.75 | |
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| 0.0037 | 16.0 | 48 | 1.4784 | 0.75 | |
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| 0.003 | 17.0 | 51 | 1.5615 | 0.75 | |
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### Framework versions |
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- Transformers 4.15.0 |
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- Pytorch 1.10.2+cu102 |
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- Datasets 1.18.2 |
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- Tokenizers 0.10.3 |
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