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Regression_BERT_NOaug_MSEloss

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distilbert
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update model card README.md

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+ ---
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+ license: apache-2.0
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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: Regression_BERT_NOaug_MSEloss
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+ results: []
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+ ---
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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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+
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+ # Regression_BERT_NOaug_MSEloss
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+
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+ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4928
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+ - Mse: 0.4928
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+ - Mae: 0.6337
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+ - R2: 0.0926
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+ - Accuracy: 0.4737
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 2e-05
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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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: 20
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R2 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 33 | 0.3184 | 0.3184 | 0.5205 | 0.0487 | 0.5946 |
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+ | No log | 2.0 | 66 | 0.2439 | 0.2439 | 0.3571 | 0.2712 | 0.7027 |
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+ | No log | 3.0 | 99 | 0.2950 | 0.2950 | 0.3792 | 0.1185 | 0.6757 |
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+ | No log | 4.0 | 132 | 0.3179 | 0.3179 | 0.4267 | 0.0503 | 0.6757 |
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+ | No log | 5.0 | 165 | 0.2869 | 0.2869 | 0.3984 | 0.1426 | 0.6757 |
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+ | No log | 6.0 | 198 | 0.2967 | 0.2967 | 0.3688 | 0.1134 | 0.7027 |
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+ | No log | 7.0 | 231 | 0.2797 | 0.2797 | 0.3599 | 0.1643 | 0.7027 |
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+ | No log | 8.0 | 264 | 0.2730 | 0.2730 | 0.3438 | 0.1844 | 0.7027 |
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+ | No log | 9.0 | 297 | 0.2813 | 0.2813 | 0.3623 | 0.1596 | 0.7027 |
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+ | No log | 10.0 | 330 | 0.2733 | 0.2733 | 0.3296 | 0.1835 | 0.7027 |
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+ | No log | 11.0 | 363 | 0.2770 | 0.2770 | 0.3432 | 0.1725 | 0.7027 |
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+ | No log | 12.0 | 396 | 0.3009 | 0.3009 | 0.3574 | 0.1010 | 0.6757 |
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+ | No log | 13.0 | 429 | 0.2735 | 0.2735 | 0.3318 | 0.1827 | 0.7027 |
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+ | No log | 14.0 | 462 | 0.2787 | 0.2787 | 0.3341 | 0.1672 | 0.7027 |
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+ | No log | 15.0 | 495 | 0.2790 | 0.2790 | 0.3312 | 0.1663 | 0.7297 |
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+ | 0.0804 | 16.0 | 528 | 0.2683 | 0.2683 | 0.3229 | 0.1984 | 0.7027 |
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+ | 0.0804 | 17.0 | 561 | 0.2749 | 0.2749 | 0.3273 | 0.1785 | 0.7297 |
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+ | 0.0804 | 18.0 | 594 | 0.2709 | 0.2709 | 0.3202 | 0.1906 | 0.7297 |
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+ | 0.0804 | 19.0 | 627 | 0.2711 | 0.2711 | 0.3205 | 0.1901 | 0.7297 |
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+ | 0.0804 | 20.0 | 660 | 0.2694 | 0.2694 | 0.3197 | 0.1950 | 0.7297 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.28.1
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+ - Pytorch 2.0.0+cu118
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+ - Datasets 2.12.0
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+ - Tokenizers 0.13.3