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--- |
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license: apache-2.0 |
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base_model: bert-base-uncased |
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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: scenario-KD-SCR-DIV2-data-glue-qnli-model-bert-base-uncased-run-1 |
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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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# scenario-KD-SCR-DIV2-data-glue-qnli-model-bert-base-uncased-run-1 |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7514 |
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- Accuracy: 0.8627 |
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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: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 32 |
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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: 6969 |
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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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| 2.4263 | 1.0 | 3273 | 1.6907 | 0.8545 | |
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| 1.7748 | 2.0 | 6547 | 1.8491 | 0.8499 | |
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| 1.1414 | 3.0 | 9820 | 1.9422 | 0.8545 | |
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| 0.8965 | 4.0 | 13094 | 1.7533 | 0.8552 | |
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| 0.7756 | 5.0 | 16367 | 1.7103 | 0.8570 | |
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| 0.6527 | 6.0 | 19641 | 1.6665 | 0.8569 | |
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| 0.6056 | 7.0 | 22914 | 1.5879 | 0.8620 | |
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| 0.5559 | 8.0 | 26188 | 1.6570 | 0.8618 | |
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| 0.5154 | 9.0 | 29461 | 1.5519 | 0.8658 | |
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| 0.4752 | 10.0 | 32735 | 1.6905 | 0.8612 | |
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| 0.4581 | 11.0 | 36008 | 1.6075 | 0.8644 | |
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| 0.4322 | 12.0 | 39282 | 1.6963 | 0.8614 | |
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| 0.3969 | 13.0 | 42555 | 1.6467 | 0.8660 | |
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| 0.393 | 14.0 | 45829 | 1.6735 | 0.8680 | |
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| 0.3651 | 15.0 | 49102 | 1.7631 | 0.8614 | |
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| 0.3464 | 16.0 | 52376 | 1.7957 | 0.8645 | |
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| 0.3455 | 17.0 | 55649 | 1.7008 | 0.8680 | |
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| 0.3276 | 18.0 | 58923 | 1.7183 | 0.8669 | |
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| 0.3239 | 19.0 | 62196 | 1.7514 | 0.8627 | |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.16.0 |
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- Tokenizers 0.15.0 |
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