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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-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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args: plus |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9148387096774193 |
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- task: |
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type: text-classification |
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name: 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: small |
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split: test |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8627272727272727 |
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verified: true |
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- name: Precision Macro |
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type: precision |
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value: 0.861664336839455 |
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verified: true |
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- name: Precision Micro |
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type: precision |
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value: 0.8627272727272727 |
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verified: true |
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- name: Precision Weighted |
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type: precision |
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value: 0.8787483927993249 |
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verified: true |
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- name: Recall Macro |
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type: recall |
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value: 0.9187704194260485 |
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verified: true |
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- name: Recall Micro |
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type: recall |
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value: 0.8627272727272727 |
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verified: true |
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- name: Recall Weighted |
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type: recall |
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value: 0.8627272727272727 |
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verified: true |
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- name: F1 Macro |
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type: f1 |
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value: 0.8842101413648463 |
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verified: true |
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- name: F1 Micro |
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type: f1 |
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value: 0.8627272727272727 |
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verified: true |
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- name: F1 Weighted |
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type: f1 |
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value: 0.8585620882832584 |
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verified: true |
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- name: loss |
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type: loss |
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value: 0.9942931532859802 |
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verified: true |
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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: 0.7760 |
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- Accuracy: 0.9148 |
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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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| 4.2994 | 1.0 | 318 | 3.3016 | 0.7442 | |
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| 2.6387 | 2.0 | 636 | 1.8892 | 0.8339 | |
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| 1.5535 | 3.0 | 954 | 1.1602 | 0.8948 | |
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| 1.0139 | 4.0 | 1272 | 0.8619 | 0.9084 | |
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| 0.7936 | 5.0 | 1590 | 0.7760 | 0.9148 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.10.2+cu102 |
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- Datasets 1.18.3 |
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- Tokenizers 0.11.6 |
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