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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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+ datasets:
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+ - clinc_oos
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: distilbert-base-uncased-distilled-clinc
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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: clinc_oos
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+ type: clinc_oos
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+ args: plus
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9487096774193549
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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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+ # distilbert-base-uncased-distilled-clinc
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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 the clinc_oos dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1580
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+ - Accuracy: 0.9487
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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: 48
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+ - eval_batch_size: 48
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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: 13
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 1.7033 | 1.0 | 318 | 1.2016 | 0.7610 |
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+ | 0.9281 | 2.0 | 636 | 0.6128 | 0.8855 |
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+ | 0.4901 | 3.0 | 954 | 0.3447 | 0.9252 |
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+ | 0.289 | 4.0 | 1272 | 0.2389 | 0.9403 |
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+ | 0.2016 | 5.0 | 1590 | 0.2000 | 0.9455 |
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+ | 0.1647 | 6.0 | 1908 | 0.1826 | 0.9484 |
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+ | 0.1446 | 7.0 | 2226 | 0.1723 | 0.9487 |
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+ | 0.1329 | 8.0 | 2544 | 0.1672 | 0.9477 |
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+ | 0.1255 | 9.0 | 2862 | 0.1639 | 0.9494 |
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+ | 0.1211 | 10.0 | 3180 | 0.1621 | 0.9497 |
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+ | 0.1171 | 11.0 | 3498 | 0.1591 | 0.95 |
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+ | 0.1149 | 12.0 | 3816 | 0.1585 | 0.9494 |
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+ | 0.1136 | 13.0 | 4134 | 0.1580 | 0.9487 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.16.2
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+ - Pytorch 2.4.1+cu121
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+ - Datasets 1.16.1
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+ - Tokenizers 0.19.1