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--- |
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license: apache-2.0 |
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base_model: distilbert-base-uncased-distilled-squad |
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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-squad-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: 0.8722580645161291 |
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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-squad-finetuned-clinc |
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This model is a fine-tuned version of [distilbert-base-uncased-distilled-squad](https://huggingface.co/distilbert-base-uncased-distilled-squad) on the clinc_oos dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.7920 |
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- Accuracy: 0.8723 |
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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: 384 |
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- eval_batch_size: 384 |
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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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| No log | 1.0 | 40 | 3.7816 | 0.2016 | |
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| No log | 2.0 | 80 | 3.3589 | 0.5374 | |
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| No log | 3.0 | 120 | 2.9695 | 0.6955 | |
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| No log | 4.0 | 160 | 2.6408 | 0.7726 | |
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| No log | 5.0 | 200 | 2.3697 | 0.8145 | |
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| No log | 6.0 | 240 | 2.1547 | 0.8426 | |
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| No log | 7.0 | 280 | 1.9912 | 0.8529 | |
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| 2.8639 | 8.0 | 320 | 1.8802 | 0.8645 | |
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| 2.8639 | 9.0 | 360 | 1.8138 | 0.8706 | |
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| 2.8639 | 10.0 | 400 | 1.7920 | 0.8723 | |
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### Framework versions |
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- Transformers 4.32.1 |
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- Pytorch 2.1.0 |
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- Datasets 2.14.6 |
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- Tokenizers 0.13.3 |
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