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--- |
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language: |
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- en |
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license: mit |
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tags: |
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- generated_from_trainer |
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- deberta-v3 |
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datasets: |
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- glue |
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metrics: |
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- accuracy |
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model-index: |
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- name: deberta-v3-small |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: GLUE SST2 |
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type: glue |
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args: sst2 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9403669724770642 |
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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) fine-tuned on SST2 |
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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 GLUE SST2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2134 |
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- Accuracy: 0.9404 |
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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: 3e-05 |
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- train_batch_size: 16 |
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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: 5.0 |
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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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| 0.176 | 1.0 | 4210 | 0.2134 | 0.9404 | |
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| 0.1254 | 2.0 | 8420 | 0.2362 | 0.9415 | |
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| 0.0957 | 3.0 | 12630 | 0.3187 | 0.9335 | |
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| 0.0673 | 4.0 | 16840 | 0.3039 | 0.9266 | |
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| 0.0457 | 5.0 | 21050 | 0.3521 | 0.9312 | |
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### Framework versions |
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- Transformers 4.13.0.dev0 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.15.1 |
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- Tokenizers 0.10.3 |
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