MathiasBrussow
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update model card README.md
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README.md
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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: 0.9503225806451613
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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: 0.2869
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- Accuracy: 0.9503
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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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- lr_scheduler_warmup_ratio: 0.026785267717638298
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- num_epochs: 24
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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 | 318 | 2.1228 | 0.7194 |
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| 2.5433 | 2.0 | 636 | 0.8036 | 0.8935 |
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| 2.5433 | 3.0 | 954 | 0.4630 | 0.9355 |
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| 0.7139 | 4.0 | 1272 | 0.3767 | 0.9429 |
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| 0.3352 | 5.0 | 1590 | 0.3417 | 0.9461 |
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| 0.3352 | 6.0 | 1908 | 0.3249 | 0.95 |
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| 0.2555 | 7.0 | 2226 | 0.3141 | 0.9487 |
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| 0.2237 | 8.0 | 2544 | 0.3089 | 0.9490 |
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| 0.2237 | 9.0 | 2862 | 0.3039 | 0.9487 |
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| 0.2098 | 10.0 | 3180 | 0.3040 | 0.9487 |
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| 0.2098 | 11.0 | 3498 | 0.2971 | 0.9516 |
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| 0.2004 | 12.0 | 3816 | 0.2945 | 0.95 |
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| 0.1949 | 13.0 | 4134 | 0.2967 | 0.9468 |
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| 0.1949 | 14.0 | 4452 | 0.2912 | 0.9497 |
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| 0.1905 | 15.0 | 4770 | 0.2907 | 0.9513 |
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| 0.1883 | 16.0 | 5088 | 0.2927 | 0.9487 |
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| 0.1883 | 17.0 | 5406 | 0.2901 | 0.9503 |
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| 0.1852 | 18.0 | 5724 | 0.2879 | 0.9497 |
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| 0.184 | 19.0 | 6042 | 0.2895 | 0.95 |
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| 0.184 | 20.0 | 6360 | 0.2876 | 0.9519 |
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| 0.1828 | 21.0 | 6678 | 0.2871 | 0.9503 |
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| 0.1828 | 22.0 | 6996 | 0.2867 | 0.9510 |
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| 0.1816 | 23.0 | 7314 | 0.2868 | 0.9503 |
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| 0.1813 | 24.0 | 7632 | 0.2869 | 0.9503 |
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### Framework versions
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- Transformers 4.16.2
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- Pytorch 2.4.1+cu121
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- Datasets 1.16.1
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- Tokenizers 0.19.1
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