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--- |
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license: mit |
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base_model: microsoft/deberta-large |
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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_large_finetuned_claimdecomp |
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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_large_finetuned_claimdecomp |
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This model is a fine-tuned version of [microsoft/deberta-large](https://huggingface.co/microsoft/deberta-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7614 |
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- Accuracy: 0.205 |
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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: 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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- training_steps: 30000 |
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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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| 1.7304 | 50.0 | 5000 | 1.7493 | 0.255 | |
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| 1.7282 | 100.0 | 10000 | 1.7495 | 0.205 | |
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| 1.7196 | 150.0 | 15000 | 1.7457 | 0.255 | |
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| 1.7107 | 200.0 | 20000 | 1.7462 | 0.255 | |
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| 1.7107 | 250.0 | 25000 | 1.7666 | 0.205 | |
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| 1.6992 | 300.0 | 30000 | 1.7614 | 0.205 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.0.0 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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