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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: distilbert-base-multilingual-cased-misogyny-sexism-decay0.01-fr-outofdomain |
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results: [] |
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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-multilingual-cased-misogyny-sexism-decay0.01-fr-outofdomain |
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This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.1385 |
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- Accuracy: 0.2369 |
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- F1: 0.1919 |
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- Precision: 0.1087 |
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- Recall: 0.8148 |
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- Mae: 0.7631 |
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- Tn: 1279 |
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- Fp: 6491 |
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- Fn: 180 |
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- Tp: 792 |
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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: 16 |
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- eval_batch_size: 16 |
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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 | F1 | Precision | Recall | Mae | Tn | Fp | Fn | Tp | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|:----:|:----:|:---:|:---:| |
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| 0.2166 | 1.0 | 2233 | 1.2875 | 0.3377 | 0.2025 | 0.1169 | 0.7562 | 0.6623 | 2217 | 5553 | 237 | 735 | |
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| 0.2068 | 2.0 | 4466 | 1.8399 | 0.3141 | 0.2154 | 0.1234 | 0.8467 | 0.6859 | 1923 | 5847 | 149 | 823 | |
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| 0.2015 | 3.0 | 6699 | 1.5430 | 0.3543 | 0.2053 | 0.1189 | 0.75 | 0.6457 | 2368 | 5402 | 243 | 729 | |
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| 0.1739 | 4.0 | 8932 | 1.8406 | 0.2815 | 0.1911 | 0.1092 | 0.7634 | 0.7185 | 1719 | 6051 | 230 | 742 | |
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| 0.163 | 5.0 | 11165 | 2.0274 | 0.2170 | 0.1957 | 0.1105 | 0.8570 | 0.7830 | 1064 | 6706 | 139 | 833 | |
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| 0.1481 | 6.0 | 13398 | 1.6407 | 0.2467 | 0.1931 | 0.1096 | 0.8107 | 0.7533 | 1369 | 6401 | 184 | 788 | |
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| 0.1334 | 7.0 | 15631 | 3.0800 | 0.1875 | 0.1953 | 0.1097 | 0.8868 | 0.8125 | 777 | 6993 | 110 | 862 | |
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| 0.12 | 8.0 | 17864 | 2.5311 | 0.2183 | 0.1962 | 0.1108 | 0.8580 | 0.7817 | 1074 | 6696 | 138 | 834 | |
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| 0.1104 | 9.0 | 20097 | 2.9522 | 0.2135 | 0.1935 | 0.1092 | 0.8488 | 0.7865 | 1041 | 6729 | 147 | 825 | |
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| 0.0938 | 10.0 | 22330 | 3.1385 | 0.2369 | 0.1919 | 0.1087 | 0.8148 | 0.7631 | 1279 | 6491 | 180 | 792 | |
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### Framework versions |
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- Transformers 4.20.1 |
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- Pytorch 1.12.0+cu102 |
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- Datasets 2.3.2 |
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- Tokenizers 0.12.1 |
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