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--- |
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license: mit |
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base_model: MoritzLaurer/deberta-v3-large-zeroshot-v2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- swag |
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metrics: |
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- accuracy |
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model-index: |
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- name: fine-tuned-MoritzLaurer-deberta-v3-large-zeroshot-v2.0-swag |
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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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# fine-tuned-MoritzLaurer-deberta-v3-large-zeroshot-v2.0-swag |
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This model is a fine-tuned version of [MoritzLaurer/deberta-v3-large-zeroshot-v2.0](https://huggingface.co/MoritzLaurer/deberta-v3-large-zeroshot-v2.0) on the swag dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5968 |
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- Accuracy: 0.9142 |
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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: 1.5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 4 |
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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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| 0.4957 | 1.0 | 4597 | 0.2545 | 0.9058 | |
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| 0.2768 | 2.0 | 9194 | 0.2780 | 0.9089 | |
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| 0.1333 | 3.0 | 13791 | 0.4016 | 0.9126 | |
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| 0.0599 | 4.0 | 18388 | 0.5968 | 0.9142 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 1.11.0 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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