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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: 0.9506451612903226
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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: 0.2466
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+ - Accuracy: 0.9506
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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: 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: 10
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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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+ | 2.9383 | 1.0 | 954 | 1.4511 | 0.8397 |
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+ | 0.8485 | 2.0 | 1908 | 0.4733 | 0.9255 |
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+ | 0.2822 | 3.0 | 2862 | 0.3070 | 0.9429 |
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+ | 0.1515 | 4.0 | 3816 | 0.2664 | 0.9490 |
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+ | 0.106 | 5.0 | 4770 | 0.2641 | 0.95 |
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+ | 0.0874 | 6.0 | 5724 | 0.2536 | 0.9510 |
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+ | 0.0764 | 7.0 | 6678 | 0.2475 | 0.9506 |
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+ | 0.0718 | 8.0 | 7632 | 0.2450 | 0.9513 |
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+ | 0.068 | 9.0 | 8586 | 0.2473 | 0.9497 |
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+ | 0.0664 | 10.0 | 9540 | 0.2466 | 0.9506 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.19.2
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+ - Pytorch 1.11.0
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+ - Datasets 1.16.1
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+ - Tokenizers 0.12.1