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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-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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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: 0.9319354838709677 |
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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-distilled-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: 0.0460 |
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- Accuracy: 0.9319 |
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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: 10 |
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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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| 0.8576 | 1.0 | 318 | 0.4512 | 0.6790 | |
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| 0.3407 | 2.0 | 636 | 0.1655 | 0.8442 | |
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| 0.1611 | 3.0 | 954 | 0.0890 | 0.9058 | |
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| 0.1046 | 4.0 | 1272 | 0.0665 | 0.9210 | |
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| 0.0831 | 5.0 | 1590 | 0.0575 | 0.9255 | |
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| 0.0727 | 6.0 | 1908 | 0.0523 | 0.9313 | |
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| 0.0664 | 7.0 | 2226 | 0.0494 | 0.9287 | |
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| 0.0625 | 8.0 | 2544 | 0.0475 | 0.9313 | |
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| 0.0603 | 9.0 | 2862 | 0.0463 | 0.9310 | |
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| 0.0589 | 10.0 | 3180 | 0.0460 | 0.9319 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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