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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: 0.9490322580645161 |
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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: 0.3032 |
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- Accuracy: 0.9490 |
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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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| 2.6314 | 1.0 | 318 | 1.8942 | 0.7274 | |
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| 1.4611 | 2.0 | 636 | 0.9553 | 0.8594 | |
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| 0.7635 | 3.0 | 954 | 0.5469 | 0.9181 | |
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| 0.4613 | 4.0 | 1272 | 0.4035 | 0.9394 | |
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| 0.3348 | 5.0 | 1590 | 0.3505 | 0.9432 | |
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| 0.2776 | 6.0 | 1908 | 0.3258 | 0.9445 | |
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| 0.2509 | 7.0 | 2226 | 0.3148 | 0.9455 | |
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| 0.236 | 8.0 | 2544 | 0.3066 | 0.9494 | |
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| 0.2282 | 9.0 | 2862 | 0.3055 | 0.9484 | |
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| 0.224 | 10.0 | 3180 | 0.3032 | 0.9490 | |
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### Framework versions |
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- Transformers 4.33.1 |
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- Pytorch 2.0.1 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.2 |
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