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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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datasets: |
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- boolq |
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metrics: |
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- accuracy |
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model-index: |
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- name: deberta-v3-large_boolq |
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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: boolq |
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type: boolq |
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config: default |
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split: validation |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.882262996941896 |
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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_boolq |
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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 boolq dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5796 |
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- Accuracy: 0.8823 |
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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: 16 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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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| No log | 0.85 | 250 | 0.3265 | 0.8740 | |
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| 0.3786 | 1.69 | 500 | 0.3212 | 0.8844 | |
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| 0.3786 | 2.54 | 750 | 0.4205 | 0.8838 | |
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| 0.1324 | 3.39 | 1000 | 0.5393 | 0.8832 | |
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| 0.1324 | 4.24 | 1250 | 0.5796 | 0.8823 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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