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README.md
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---
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license: apache-2.0
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base_model: distilbert-base-uncased
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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-finetuned-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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config: plus
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split: validation
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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: 0.9190322580645162
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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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# distilbert-base-uncased-finetuned-clinc
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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: 0.7683
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- Accuracy: 0.9190
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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: 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: 5
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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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| 4.2971 | 1.0 | 318 | 3.2827 | 0.7152 |
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| 2.6163 | 2.0 | 636 | 1.8665 | 0.84 |
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| 1.5389 | 3.0 | 954 | 1.1485 | 0.8981 |
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| 1.0054 | 4.0 | 1272 | 0.8495 | 0.9135 |
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| 0.7912 | 5.0 | 1590 | 0.7683 | 0.9190 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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