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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-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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args: plus |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9387096774193548 |
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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: 0.0878 |
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- Accuracy: 0.9387 |
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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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| 1.0369 | 1.0 | 318 | 0.5902 | 0.6987 | |
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| 0.4468 | 2.0 | 636 | 0.2434 | 0.8606 | |
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| 0.2204 | 3.0 | 954 | 0.1412 | 0.9113 | |
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| 0.1478 | 4.0 | 1272 | 0.1121 | 0.9252 | |
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| 0.1206 | 5.0 | 1590 | 0.1010 | 0.93 | |
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| 0.1086 | 6.0 | 1908 | 0.0947 | 0.9345 | |
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| 0.1009 | 7.0 | 2226 | 0.0916 | 0.9368 | |
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| 0.0966 | 8.0 | 2544 | 0.0896 | 0.9381 | |
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| 0.0939 | 9.0 | 2862 | 0.0881 | 0.9390 | |
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| 0.0928 | 10.0 | 3180 | 0.0878 | 0.9387 | |
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### Framework versions |
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- Transformers 4.11.3 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 1.16.1 |
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- Tokenizers 0.10.3 |
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